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Balijepalli, Narasimha Chandrasekhar. "Stochastic process models for dynamic traffic assignment." Thesis, University of Leeds, 2007. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.436385.
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Chu, Qin. "Dynamic and stochastic models for container allocation." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/11742.
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Corneli, Marco. "Dynamic stochastic block models, clustering and segmentation in dynamic graphs." Thesis, Paris 1, 2017. http://www.theses.fr/2017PA01E012/document.
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Cette thèse porte sur l’analyse de graphes dynamiques, définis en temps discret ou continu. Nous introduisons une nouvelle extension dynamique du modèle a blocs stochastiques (SBM), appelée dSBM, qui utilise des processus de Poisson non homogènes pour modéliser les interactions parmi les paires de nœuds d’un graphe dynamique. Les fonctions d’intensité des processus ne dépendent que des classes des nœuds comme dans SBM. De plus, ces fonctions d’intensité ont des propriétés de régularité sur des intervalles temporels qui sont à estimer, et à l’intérieur desquels les processus de Poisson redeviennent homogènes. Un récent algorithme d’estimation pour SBM, qui repose sur la maximisation d’un critère exact (ICL exacte) est ici adopté pour estimer les paramètres de dSBM et sélectionner simultanément le modèle optimal. Ensuite, un algorithme exact pour la détection de rupture dans les séries temporelles, la méthode «pruned exact linear time» (PELT), est étendu pour faire de la détection de rupture dans des données de graphe dynamique selon le modèle dSBM. Enfin, le modèle dSBM est étendu ultérieurement pour faire de l’analyse de réseau textuel dynamique. Les réseaux sociaux sont un exemple de réseaux textuels: les acteurs s’échangent des documents (posts, tweets, etc.) dont le contenu textuel peut être utilisé pour faire de la classification et détecter la structure temporelle du graphe dynamique. Le modèle que nous introduisons est appelé «dynamic stochastic topic block model» (dSTBM)This thesis focuses on the statistical analysis of dynamic graphs, both defined in discrete or continuous time. We introduce a new extension of the stochastic block model (SBM) for dynamic graphs. The proposed approach, called dSBM, adopts non homogeneous Poisson processes to model the interaction times between pairs of nodes in dynamic graphs, either in discrete or continuous time. The intensity functions of the processes only depend on the node clusters, in a block modelling perspective. Moreover, all the intensity functions share some regularity properties on hidden time intervals that need to be estimated. A recent estimation algorithm for SBM, based on the greedy maximization of an exact criterion (exact ICL) is adopted for inference and model selection in dSBM. Moreover, an exact algorithm for change point detection in time series, the "pruned exact linear time" (PELT) method is extended to deal with dynamic graph data modelled via dSBM. The approach we propose can be used for change point analysis in graph data. Finally, a further extension of dSBM is developed to analyse dynamic net- works with textual edges (like social networks, for instance). In this context, the graph edges are associated with documents exchanged between the corresponding vertices. The textual content of the documents can provide additional information about the dynamic graph topological structure. The new model we propose is called "dynamic stochastic topic block model" (dSTBM).Graphs are mathematical structures very suitable to model interactions between objects or actors of interest. Several real networks such as communication networks, financial transaction networks, mobile telephone networks and social networks (Facebook, Linkedin, etc.) can be modelled via graphs. When observing a network, the time variable comes into play in two different ways: we can study the time dates at which the interactions occur and/or the interaction time spans. This thesis only focuses on the first time dimension and each interaction is assumed to be instantaneous, for simplicity. Hence, the network evolution is given by the interaction time dates only. In this framework, graphs can be used in two different ways to model networks. Discrete time […] Continuous time […]. In this thesis both these perspectives are adopted, alternatively. We consider new unsupervised methods to cluster the vertices of a graph into groups of homogeneous connection profiles. In this manuscript, the node groups are assumed to be time invariant to avoid possible identifiability issues. Moreover, the approaches that we propose aim to detect structural changes in the way the node clusters interact with each other. The building block of this thesis is the stochastic block model (SBM), a probabilistic approach initially used in social sciences. The standard SBM assumes that the nodes of a graph belong to hidden (disjoint) clusters and that the probability of observing an edge between two nodes only depends on their clusters. Since no further assumption is made on the connection probabilities, SBM is a very flexible model able to detect different network topologies (hubs, stars, communities, etc.)
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Nori, Vijay S. "Algorithms for dynamic and stochastic logistics problems." Diss., Georgia Institute of Technology, 1999. http://hdl.handle.net/1853/24513.
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Paltrinieri, Federico. "Modeling temporal networks with dynamic stochastic block models." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18805/.
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Osservando il recente interesse per le reti dinamiche temporali e l'ampio numero di campi di applicazione, questa tesi ha due principali propositi: primo, di analizzare alcuni modelli teorici di reti temporali, specialmente lo stochastic blockmodel dinamico, al fine di descrivere la dinamica di sistemi reali e fare previsioni. Il secondo proposito della tesi è quello di creare due nuovi modelli teorici, basati sulla teoria dei processi autoregressivi, dai quali inferire nuovi parametri dalle reti temporali, come la matrice di evoluzione di stato e una migliore stima della varianza del rumore del processo di evoluzione temporale. Infine, tutti i modelli sono testati su un data set interbancario: questi rivelano la presenza di un evento atteso che divide la rete temporale in due periodi distinti con differenti configurazioni e parametri.
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Chung, Kun-Jen. "Some topics in risk-sensitive stochastic dynamic models." Diss., Georgia Institute of Technology, 1985. http://hdl.handle.net/1853/28644.
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Loddo, Antonello. "Bayesian analysis of multivariate stochastic volatility and dynamic models." Diss., Columbia, Mo. : University of Missouri-Columbia, 2006. http://hdl.handle.net/10355/4359.
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Thesis (Ph.D.)--University of Missouri-Columbia, 2006.The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (April 26, 2007) Vita. Includes bibliographical references.
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Foliente, Greg C. "Stochastic dynamic response of wood structural systems." Diss., This resource online, 1993. http://scholar.lib.vt.edu/theses/available/etd-05042006-164535/.
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Ahn, Kwangwon. "Dynamic stochastic general equilibrium models with money, default and collateral." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:78317412-e13d-4495-9665-340e777ab7b2.
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This D.Phil. dissertation investigates the areas in financial stability. The three comprising essays have a common ground: money, default and collateral in the theory of finance. Chapter Two (co-authored with Prof. Dimitrios Tsomocos), which is titled “A Dynamic General Equilibrium Model to Analyse Financial Stability”, aims to refine and improve existing DSGE models in two ways. First, it incorporates hitherto neglected components such as endogenous default, money via cash-in-advance constraints and heterogeneous banking sectors. Thus, in contrast to the New Keynesian approach, here it is liquidity and default that are the driving forces behind our results. Second, in focusing on both monetary policy and fiscal policy, it elucidates how interactions between the two policy arenas affect macroeconomic fluctuations, particularly in regard to financial stability. Through these refinements, we put forward the policy response necessary to achieve a stable financial system using a calibrated DSGE model. Chapter Three, entitled “Monetary Policy in a Time of Natural Disaster”, investigates the appropriate monetary policy response to natural disasters in the DSGE framework. I develop a realistic model for financial turmoil by evaluating the impact of natural disasters on credit markets by including financial frictions such as endogenous default and liquidity constraints. I show that the standard Taylor rule (1993) response in models with money and default is to increase the nominal interest rate after a disaster shock. However, in fact an inflation-targeting policy (i.e. monetary contraction) is not compatible with mitigating financial fragility in the highly indebted economy with near-zero interest rate, and arguably the `Taylor Principle' does not hold in such as economy (e.g. Japan in 2011). Nevertheless, expansionary monetary policy induces a debt overhang even further. Chapter Four, “Collateral, Default and Asset Prices”, uses a DSGE framework to put forward a model of how agents adjust their asset holdings in response to deflationary shocks. By introducing collateral constraints in the default decision, I capture some original features of the early debt-deflation literature, such as distress selling and instability. The estimated model successfully delivers a procyclical feedback loop for the default channel, which consists of foreclosure, high borrowing costs, inefficient capital allocation, and a further decrease in the output level. I investigated recessionary shocks inducing deflation in commodity and/or asset prices for monetary policy experiments. This, therefore, underlines the importance of monetary policy in restoring financial stability during a deflationary period.
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Cherepnev, Alexey [Verfasser]. "Stochastic foundations of dynamic trade and labor market models / Alexey Cherepnev." Mainz : Universitätsbibliothek der Johannes Gutenberg-Universität Mainz, 2015. http://d-nb.info/1225685508/34.
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Povoledo, Laura. "Dynamic stochastic general equilibrium models for the study of economic fluctuations." Thesis, University College London (University of London), 2005. http://discovery.ucl.ac.uk/1445796/.
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The thesis applies a variety of DSGE models to a set of problems whose common link is the analysis of economic fluctuations. The DSGE methodology is applied first to the analysis of economic fluctuations in Italy. After documenting' the crucial features of economic fluctuations in Italy (high volatility of hours worked and low volatility of employment), the thesis explains why the standard RBC model cannot reproduce them. Therefore, a modified RBC model with labour adjustment costs and an underground sector is introduced, and its performance analysed. Then, the thesis utilizes DSGE theory to study how fluctuations are transmitted within and between countries. Using a two-country general equilibrium model with monopolistic competition and sticky prices, it examines first the relative effects of a wide range (money, supply and demand) of shocks, and then the aggregate effects separately. The relative effects are the consequences of shocks for the relative price and quantities of domestic tradeables versus nontradeables. The main finding is that not only sector- specific shocks affect these relative prices and allocations, but also aggregate monetary shocks, thus contributing to explain why money has sectoral effects, as in the empirical literature. The aggregate effects are the consequences of shocks for the main macroeconomic variables. The analysis of the aggregate effects differs from the most recent literature because: 1) the role of critical parameters in the transmission is analysed simultaneously 2) the analysis is not confined to monetary shocks 3) supply and demand shocks are disaggregated by sector 4) the assumptions that the marginal productivity of labour may be decreasing, and that individuals cannot work in both sectors, are introduced. The aggregate effects of the shocks depend on the choice of parameters. The assump tion that individuals cannot work in both sectors leads to a lower elasticity of marginal costs with respect to output.
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Imura, Yuko. "Endogenous Trade Participation in Multi-Country Dynamic Stochastic General Equilibrium Models." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1338303765.
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Schlosser, Rainer. "Six essays on stochastic and deterministic dynamic pricing and advertising models." Doctoral thesis, Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät, 2014. http://dx.doi.org/10.18452/16973.
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Die kumulative Dissertation beschäftigt sich mit stochastischen und deterministischen dynamischen Verkaufsmodellen für langlebige sowie verderbliche Güter. Die analysierten dynamischen Modelle sind durch die Möglichkeit der simultanen Variation von Preis und Werbung in stetiger Zeit charakterisiert und folgen den aktuellen Entwicklungen der Dynamischen Preissetzung. Dabei steht die Berücksichtigung und Analyse von (i) Zeitinhomogenitäten, (ii) Adoptionseffekten, (iii) Oligopolwettbewerb und (iv) der Risikoaversion des Entscheiders im Zentrum der Arbeit. Für die Spezialfälle isoelastischer und exponentieller Nachfrage in Verbindung mit isoelastischer Werbewirkung gelingt es explizite Lösungen der optimalen Preis- und Werbekontrollen herzuleiten. Die optimal gesteuerten Verkaufsprozesse können analytisch beschrieben und ausgewertet werden. Insbesondere werden neben erwarteten Preis- und Restbestandsentwicklungen auch assoziierte Gewinnverteilungen untersucht und Sensitivitätsresultate hergeleitet. Darüber hinaus wird analysiert unter welchen Bedingungen monopolistische Strategien sozial effizient sind und welche Besteuerungs- und Subventionsmechanismen geeignet sind um Effizienz herzustellen. Die Ergebnisse sind in sechs Artikel gefasst und bieten ökonomische Einsichten in verschiedene praktische Verkaufsanwendungen, speziell im Bereich des elektronischen Handels.The cumulative dissertation deals with stochastic and deterministic dynamic sales models for durable as well as perishable products. The models analyzed are characterized by simultaneous dynamic pricing and advertising controls in continuous time and are in line with recent developments in dynamic pricing. They include the modeling of multi-dimensional decisions and take (i) time dependencies, (ii) adoption effects (iii), competitive settings and (iv) risk aversion, explicitly into account. For special cases with isoelastic demand functions as well as with exponential ones explicit solution formulas of the optimal pricing and advertising feedback controls are derived. Moreover, optimally controlled sales processes are analytically described. In particular, the distribution of profits, the expected evolution of prices as well as inventory levels are analyzed in detail and sensitivity results are obtained. Furthermore, we consider the question whether or not monopolistic policies are socially efficient; in special cases, we propose taxation/subsidy mechanisms to establish efficiency. The results are presented in six articles and provide economic insights into a variety of dynamic sales applications of the business world, especially in the area of e-commerce.
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Giampieri, Enrico <1983>. "Stochastic models and dynamic measures for the characterization of bistable circuits." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2012. http://amsdottorato.unibo.it/4298/1/tesi_phd.pdf.
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During the last few years, a great deal of interest has risen concerning the applications of stochastic methods to several biochemical and biological phenomena.
Phenomena like gene expression, cellular memory, bet-hedging strategy in bacterial growth and many others, cannot be described by continuous stochastic models due to their intrinsic discreteness and randomness. In this thesis I have used the Chemical Master Equation (CME) technique to modelize some feedback cycles and analyzing their properties, including experimental data.
In the first part of this work, the effect of stochastic stability is discussed on a toy model of the genetic switch that triggers the cellular division, which malfunctioning is known to be one of the hallmarks of cancer.
The second system I have worked on is the so-called futile cycle, a closed cycle of two enzymatic reactions that adds and removes a chemical compound, called phosphate group, to a specific substrate. I have thus investigated how adding noise to the enzyme (that is usually in the order of few hundred molecules) modifies the probability of observing a specific number of phosphorylated substrate molecules, and confirmed theoretical predictions with numerical simulations. In the third part the results of the study of a chain of multiple phosphorylation-dephosphorylation cycles will be presented. We will discuss an approximation method for the exact solution in the bidimensional case and the relationship that this method has with the thermodynamic properties of the system, which is an open system far from equilibrium.In the last section the agreement between the theoretical prediction of the total protein quantity in a mouse cells population and the observed quantity will be shown, measured via fluorescence microscopy.
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Giampieri, Enrico <1983>. "Stochastic models and dynamic measures for the characterization of bistable circuits." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2012. http://amsdottorato.unibo.it/4298/.
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During the last few years, a great deal of interest has risen concerning the applications of stochastic methods to several biochemical and biological phenomena.
Phenomena like gene expression, cellular memory, bet-hedging strategy in bacterial growth and many others, cannot be described by continuous stochastic models due to their intrinsic discreteness and randomness. In this thesis I have used the Chemical Master Equation (CME) technique to modelize some feedback cycles and analyzing their properties, including experimental data.
In the first part of this work, the effect of stochastic stability is discussed on a toy model of the genetic switch that triggers the cellular division, which malfunctioning is known to be one of the hallmarks of cancer.
The second system I have worked on is the so-called futile cycle, a closed cycle of two enzymatic reactions that adds and removes a chemical compound, called phosphate group, to a specific substrate. I have thus investigated how adding noise to the enzyme (that is usually in the order of few hundred molecules) modifies the probability of observing a specific number of phosphorylated substrate molecules, and confirmed theoretical predictions with numerical simulations. In the third part the results of the study of a chain of multiple phosphorylation-dephosphorylation cycles will be presented. We will discuss an approximation method for the exact solution in the bidimensional case and the relationship that this method has with the thermodynamic properties of the system, which is an open system far from equilibrium.In the last section the agreement between the theoretical prediction of the total protein quantity in a mouse cells population and the observed quantity will be shown, measured via fluorescence microscopy.
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Cheng, Gang. "Analyzing and Solving Non-Linear Stochastic Dynamic Models on Non-Periodic Discrete Time Domains." TopSCHOLAR®, 2013. http://digitalcommons.wku.edu/theses/1236.
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Stochastic dynamic programming is a recursive method for solving sequential or multistage decision problems. It helps economists and mathematicians construct and solve a huge variety of sequential decision making problems in stochastic cases. Research on stochastic dynamic programming is important and meaningful because stochastic dynamic programming reflects the behavior of the decision maker without risk aversion; i.e., decision making under uncertainty. In the solution process, it is extremely difficult to represent the existing or future state precisely since uncertainty is a state of having limited knowledge. Indeed, compared to the deterministic case, which is decision making under certainty, the stochastic case is more realistic and gives more accurate results because the majority of problems in reality inevitably have many unknown parameters. In addition, time scale calculus theory is applicable to any field in which a dynamic process can be described with discrete or continuous models. Many stochastic dynamic models are discrete or continuous, so the results of time scale calculus are directly applicable to them as well. The aim of this thesis is to introduce a general form of a stochastic dynamic sequence problem on complex discrete time domains and to find the optimal sequence which maximizes the sequence problem.
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Erasmus, Gert Botha. "Stochastic models of steady state and dynamic operation of systems of congestion." Thesis, Pretoria : [s.n.], 2006. http://hdl.handle.net/2263/28814.
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(i) The thesis sets out to address the problematic phenomenon of Systems of Congestion via Basic Queueing Theory. The theory, and its application in practice, appears to be a field of study which is the common domain of “theorists” and “practitioners”. (ii) This professional dichotomy has come about due to diverging interests in that one group is mainly interested in the purity of mathematical modelling, and the other group is motivated to use modelling, which conveniently employs applications oriented solutions. (iii) The schism between the groups has been accentuated by the “practitioners” who in addition to having an interest in steady state system behaviour make use of methods of modelling of the transient operation of complex Systems of Congestion. (iv) At the outset the thesis demonstrates how closed form solutions are obtained for steady state and transient state operation of a selection of Systems of Congestion. The attendant mathematical derivations are elegant and intricate. (v) Having revealed the limited utility of closed-form solutions the thesis proceeds to investigate the feasibility of using dynamical systems theory to study the transient behaviour of complex Systems of Congestion. (vi) The creation of Chaos Theory in recent decades suggests that it may be employed as a useful tool in analysing Systems of Congestion. Iterative Chaos Theory methods of orbit generation for complete Systems of Congestion are therefore examined. The use of such orbit generation methods is found to be satisfactory for simple Systems of Congestion. More than a perfunctory knowledge of chaos mapping is however required. The simplicity of modelling is emphasized. (vii) Based on the results of benchmarking the creation of dynamic system orbits against an existing simulation method, the research advances to modelling of the transient operation of complex systems. Once again the iterative method of orbit generation displays the ease of modelling while simultaneously unfolding system dynamics graphically. (viii) One may hopefully contend that a tool of eminent utility has been developed to aid practitioners in studying and optimizing Systems of Congestion.Thesis (PhD (Industrial Engineering))--University of Pretoria, 2006.
Industrial and Systems Engineering
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Chan, Antoni Bert. "Beyond dynamic textures a family of stochastic dynamical models for video with applications to computer vision /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2008. http://wwwlib.umi.com/cr/ucsd/fullcit?p3331461.
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Thesis (Ph. D.)--University of California, San Diego, 2008.Title from first page of PDF file (viewed December 16, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 259-271).
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Bastani, Spencer, and Olov Andersson. "Stochastic Optimization in Dynamic Environments : with applications in e-commerce." Thesis, Linköping University, Department of Mathematics, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8509.
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In this thesis we address the problem of how to construct an optimal algorithm for displaying banners (i.e advertisements shown on web sites). The optimization is based on the revenue each banner generates, with the aim of selecting those banners which maximize future total revenue. Banner optimality is of major importance in the e-commerce industry, in particular on web sites with heavy traffic. The 'micropayments' from showing banners add up to substantial profits due to the large volumes involved. We provide a broad, up-to-date and primarily theoretical treatment of this global optimization problem. Through a synthesis of mathematical modeling, statistical methodology and computer science we construct a stochastic 'planning algorithm'. The superiority of our algorithm is based on empirical analysis conducted by us on real internet-data at TradeDoubler AB, as well as test-results on a selection of stylized data-sets. The algorithm is flexible and adapts well to new environments.
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Fujiwara, Ippei. "Three essays on dynamic general equilibrium models." Thesis, University of Oxford, 2009. http://ora.ox.ac.uk/objects/uuid:b963d031-cd68-4bee-91b7-4541e5d600d2.
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This thesis aims at contributing to the existing studies in the dynamic stochastic general equilibrium model, particularly in the new Keynesian models, on three aspects. It consists of three chapters. Chapter 2 is on “Dynamic new Keynesian Life-Cycle Model.” Chapter 3 is on “Re-thinking Price Stability in an Economy with Endogenous Firm Entry: Real Imperfections under Product Variety.” Chapter 4 is on “Growth Expectation.” Abstracts of each Chapter are as follows. In Chapter 2, we first construct a dynamic new Keynesian model that incorporates life-cycle behavior a la Gertler (1999), in order to study whether structural shocks to the economy have asymmetric effects on heterogeneous agents, namely workers and retirees. We also examine whether considerations of life-cycle and demographic structure alter the dynamic properties of the monetary business cycle model, specifically the degree of amplification in impulse responses. According to our simulation results, shocks indeed have asymmetric impacts on different households and the demographic structure does alter the size of responses against shocks by changing the trade-off between substitution and income effects. In Chapter 3, we re-think price stability in an economy with endogenous firm entry under possible distortions. We first demonstrate that endogenous entry causes real imperfections. Reflecting fluctuations in the number of varieties, the gap between the natural and the efficient level of output is no longer constant and variant to shocks. As a result, the central bank faces a trade-off between stabilizing inflation and welfare-relevant output gap. Then, we show that this results in the non-zero optimal rate of inflation. We further check whether welfare can be enhanced by targeting welfare-based inflation instead of cross-sectional average inflation contrary to the previous findings. Simulations even with such distortions as unknown natural interest rate or no fiscal remedy for efficient non-stochastic steady states, however, support cross-sectional average inflation targeting although there may exist some small gains by referring also to welfare-based inflation rates. Incomplete stabilization may enhance welfare in an economy when agents cannot internalize the externality on the love for variety. Chapter 4 is about the difficulty in producing reasonable business cycles for the expectation shock about higher future technology. For a long time, changes in expectations about the future have been thought to be significant sources of economic fluctuations, as argued by Pigou (1926). Although creating such an expectation-driven cycle (the Pigou cycle) in equilibrium business cycle models was considered to be a difficult challenge, as pointed out by Barro and King (1984), recently, several researchers have succeeded in producing the Pigou cycle by balancing the tension between the wealth effect and the substitution effect stemming from the higher expected future productivity. Seminal research by Christiano et al. (2007a) explains the “stock market boom-bust cycles,” characterized by increases in consumption, labor inputs, investment and the stock prices relating to high expected future technology levels, by introducing investment growth adjustment costs, habit formation in consumption, sticky prices and an inflation-targeting central bank. We, however, show that such a cycle is difficult to generate based on “growth expectation,” which reflect expectations of higher productivity growth rates. Thus, Barro and King’s (1984) prediction still applies.
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Körner, Jenny [Verfasser], and Jürgen [Akademischer Betreuer] Jerger. "Macroprudential Regulation in Dynamic Stochastic General Equilibrium Models / Jenny Körner ; Betreuer: Jürgen Jerger." Regensburg : Universitätsbibliothek Regensburg, 2017. http://d-nb.info/1139892355/34.
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Mustafayev, Elchin. "Policy interactions, uncertainty, and credit cycles in financial dynamic stochastic general equilibrium models." Thesis, University of Nottingham, 2018. http://eprints.nottingham.ac.uk/53227/.
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This dissertation joins a vibrant conversation in macroeconomics about the role of financial frictions in business cycles spurred on by the recent financial crisis. Our proposed study contributes to this lively debate in a fundamental way by putting forward two DSGE models. Firstly, we consider a DSGE model which accounts for the financial sector and assumes a distorted steady state. Unlike in studies where the welfare effects of distinct policy bodies i.e. the central bank and the macroprudential institution are not tracked, in our proposed model we derive welfare-based loss functions that trace associated inefficiencies emerging from both nominal and financial distortions. Therefore, to the best of our knowledge, this model is the first to consider welfare-based mandates to the central bank and the macroprudential institution that targets related inefficiencies. In addition, a key innovation of this model is the use of such welfare-based mandate in a game-theoretical framework. Secondly, we introduce a DSGE model, which in addition to financial frictions, is augmented with stochastic volatility and nominal rigidities. This model is then used to assess the effectiveness of conventional, unconventional monetary policies and macroprudential policies in mitigating the effects of disturbances in the presence of risk shocks. To the best of our knowledge, this second model is the first to analyse the effectiveness of unconventional monetary policy and macroprudential policies with stochastic volatility. Furthermore, another key novelty of our research is the analysis of the interactions between three policy options, namely conventional, unconventional monetary and macroprudential policies.
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Oh, Jonghyeon. "Essays on Business Cycles and Dynamic Stochastic General Equilibrium Models with Heterogeneous Agents." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1397790687.
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BELOUSOVA, IRINA. "The role of endogenous capital depreciation rate in Dynamic Stochastic General Equilibrium models." Doctoral thesis, Università Politecnica delle Marche, 2017. http://hdl.handle.net/11566/251113.
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L’obiettivo principale della tesi è quello di costruire e stimare un modello DSGE in cui si ipotizza un tasso di deprezzamento del capitale variabile nel tempo e si introduce come variable di controllo la manutenzione e riparazione dei beni e servizi. A tal fine viene definita esplicitamente una funzione di deprezzamento correlata positivamente con il tasso di utilizzo del capitale e negativamente con la manutenzione. Dalle condizioni di equilibrio del modello analitico ne deriva che il deprezzamento presenta un trend di crescita nel tempo il quale, in steady state, dipende dallo shock tecnologico agli investimenti specifici. In generale, vengono inclusi nel modello tre tipi di progressi tecnologici: lo shock di produzione neutrale (labor augmenting), lo shock agli investimenti specifici (IST), e lo shock all’efficienza marginale degli investimenti (MEI). Il modello con il deprezzamento endogeno e la manutenzione viene confrontato con il modello base in cui il deprezzamento è costante e la manutenzione è esclusa. Quest’ultimo è costruito sulla base del modello di Justiniano et al. (2011). I risultati di stima del modello con la manutenzione, effettuata sull’economia del Canada, confermano le asserzioni di Justiniano et al. (2011) secondo i quali lo shock all’efficienza marginale degli investimenti (MEI) è il maggior responsabile delle fluttuazioni economiche. Al contrario, lo shock IST risulta essere trascurabile. A differenza sia del modello base che del modello di Justiniano et al. (2011), in risposta allo MEI shock il modello con la manutenzione genera comportamenti ottimali prociclici in tutte le principali variabili macroeconomiche, compreso il consumo. Quest’ultimo, infatti, è controciclico negli altri due modelli. Inoltre, nel modello con la manutenzione le dinamiche ottimali di convergenza delle principali variabili endogene sono amplificate ed il ritorno all’equilibrio di steady state è ritardato. Ciò è dovuto alla presenza del deprezzamento endogeno che a causa dell’obsolescenza aumenta e distrugge così una parte del capitale installato. Nel modello con la manutenzione, inoltre, viene introdotto uno shock nuovo che impatta sul processo di trasformazione dei beni e servizi di manutenzione, lo shock specifico alla manutenzione (MST). Secondo i risultati di stima, nel lungo periodo tale shock non ha alcun potere esplicativo delle variazioni nelle principali variabili endogene, eccetto un impatto trascurabile sulla crescita della manutenzione. Nel breve periodo, tuttavia, tale shock è il maggior responsabile delle variazioni nella manutenzione.The main objective of the thesis is to build and estimate a Dynamic Stochastic General Equilibrium model, in which it is assumed a variable depreciation rate of physical capital and introduced maintenance and repair goods and services as a control variable of the agents. We define an explicit depreciation rate function which is positively related with capital utilization rate and negatively related with maintenance to capital ratio. Along the balanced growth path depreciation rate exhibits a growth trend given by the steady state value of the investment-specific technology progress. We include three types of technological progresses: the labor augmenting technology progress, the investment-specific technology progress (IST) and the marginal efficiency of investment technology progress (MEI). We compare the model with endogenous depreciation and maintenance sector to our baseline DSGE model, which is built following Justiniano et al. (2011). The estimation exercises of our maintenance model, performed on the Canadian economy, confirm the results of Justiniano et al. (2011) according to which the main driver of the business cycle fluctuations is the shock to the marginal efficiency of investment whereas the role of the IST shock is negligible. In response to the MEI shock our model is able to generate co-movement in all the considered real endogenous variables including consumption which in Justiniano et al. (2011) behaves counter cyclically. The optimal paths result to be amplified and convergence is delayed as a consequence of increased depreciation due to obsolescence, which destroys part of installed capital. We as well include in our model a shock which affects the transformation process of the maintenance goods, named the maintenance-specific technology progress. In long run this shock is found to have no effect in the variations of the main real variables except of a low effect on the maintenance growth. On the contrary, it becomes the key-driver of maintenance growth in short run.
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Lenormand, Maxime. "Initialize and Calibrate a Dynamic Stochastic Microsimulation Model: Application to the SimVillages Model." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2012. http://tel.archives-ouvertes.fr/tel-00764929.
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Le but de cette thèse est de développer des outils statistiques permettant d'initialiser et de calibrer les modèles de microsimulation dynamique stochastique, en partant de l'exemple du modèle SimVillages (développé dans le cadre du projet Européen PRIMA). Ce modèle couple des dynamiques démographiques et économiques appliquées à une population de municipalités rurales. Chaque individu de la population, représenté explicitement dans un ménage au sein d'une commune, travaille éventuellement dans une autre, et possède sa propre trajectoire de vie. Ainsi, le modèle inclut-il des dynamiques de choix de vie, d'étude, de carrière, d'union, de naissance, de divorce, de migration et de décès. Nous avons développé, implémenté et testé les modèles et méthodes suivants: * un modèle permettant de générer une population synthétique à partir de données agrégées, où chaque individu est membre d'un ménage, vit dans une commune et possède un statut au regard de l'emploi. Cette population synthétique est l'état initial du modèle. * un modèle permettant de simuler une table d'origine-destination des déplacements domicile-travail à partir de données agrégées. * un modèle permettant d'estimer le nombre d'emplois dans les services de proximité dans une commune donnée en fonction de son nombre d'habitants et de son voisinage en termes de service. * une méthode de calibration des paramètres inconnus du modèle SimVillages de manière à satisfaire un ensemble de critères d'erreurs définis sur des sources de données hétérogènes. Cette méthode est fondée sur un nouvel algorithme d'échantillonnage séquentiel de type Approximate Bayesian Computation.
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Wong, Wee Chin. "Estimation and control of jump stochastic systems." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31775.
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Thesis (Ph.D)--Chemical Engineering, Georgia Institute of Technology, 2010.Committee Chair: Jay H. Lee; Committee Member: Alexander Gray; Committee Member: Erik Verriest; Committee Member: Magnus Egerstedt; Committee Member: Martha Grover; Committee Member: Matthew Realff. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Uyar, Emrah. "Routing in stochastic environments." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26554.
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Thesis (Ph.D)--Industrial and Systems Engineering, Georgia Institute of Technology, 2009.Committee Co-Chair: Erera, Alan L.; Committee Co-Chair: Savelsbergh, Martin W. P.; Committee Member: Ergun, Ozlem; Committee Member: Ferguson, Mark; Committee Member: Kleywegt, Anton J.. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Kastner, Gregor, Sylvia Frühwirth-Schnatter, and Hedibert Freitas Lopes. "Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models." WU Vienna University of Economics and Business, 2016. http://epub.wu.ac.at/4875/1/research_report_updated.pdf.
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We discuss efficient Bayesian estimation of dynamic covariance matrices in multivariate time series through a factor stochastic volatility model. In particular, we propose two interweaving strategies (Yu and Meng, Journal of Computational and Graphical Statistics, 20(3), 531-570, 2011) to substantially accelerate convergence and mixing of standard MCMC approaches. Similar to marginal data augmentation techniques, the proposed acceleration procedures exploit non-identifiability issues which frequently arise in factor models. Our new interweaving strategies are easy to implement and come at almost no extra computational cost; nevertheless, they can boost estimation efficiency by several orders of magnitude as is shown in extensive simulation studies. To conclude, the application of our algorithm to a 26-dimensional exchange rate data set illustrates the superior performance of the new approach for real-world data.Series: Research Report Series / Department of Statistics and Mathematics
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Zaidi, Salman [Verfasser]. "System Identification of Stochastic Nonlinear Dynamic Systems using Takagi-Sugeno Fuzzy Models / Salman Zaidi." Kassel : Kassel University Press, 2019. http://d-nb.info/118450279X/34.
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Kotze, Kevin Lawrence. "The South African business cycle and the application of dynamic stochastic general equilibrium models." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/96055.
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Thesis (PhD)--Stellenbosch University, 2014.ENGLISH ABSTRACT: This dissertation considers the use of Dynamic Stochastic General Equilibrium (DSGE) models for the analysis of South African macroeconomic business cycle phenomena. It includes four separate, but interrelated parts, which follow a logical sequence. The rst part motivates the use of these models before establishing the theoretical foundations for these models. The theoretical foundations are accompanied by detailed derivations that are used to construct a model for a small open economy. The second part considers the properties of South African macroeconomic data that may be used to estimate the parameters in these models. It includes a discussion of the variables that may be included in such a model, as well as various methods that may be used to extract the business cycle. Thereafter, the sample size for the dataset is established, after investigating for possible structural breaks in the rst two moments of the data, using various univariate and multivariate techniques. The nal chapter of this part contains an investigation into the measures of core in ation, whereby a comparison of trimmed means, dynamic factor models and various wavelet decompositions are applied to data for South Africa. The third part considers the application of the dataset that was identi ed in part two, in a DSGE model that incorporates features that are typical of small open economies. It includes a discussion that relates to the role of the exchange rate in these models, which is found to contain key information. In addition, this part also includes a optimal policy investigation, which considers the reaction function of central bank. The nal part of this thesis considers more recent advances that have been applied to DSGE models for the South African economy. It includes an example of a nonlinear model that is estimated with the aid of a particle lter, which is then used for forecasting purposes. The forecasting results of both linear and nonlinear versions of the model are then compared with the results from various Vector Autoregression (VAR) and Bayesian VAR models.
AFRIKAANSE OPSOMMING: Hierdie proefskrif oorweeg die gebruik van Dinamiese Stogastiese Algemene Ewewig (Engels: Dynamic Stochastic General Equilibrium (DSGE)) modelle vir die analise van besigheidsiklus gebeure in die Suid Afrikaanse makroekonomie. Dit bestaan uit vier aparte dog onderling verwante dele wat in « logiese ontwikkeling vorm. Die eerste deel motiveer die gebruik van dié modelle en daarna word die teoretiese onderbou van die modelle daargestel. Die teoretiese onderbou word aangevul met gedetaileerde stappe van die a eiding van die verhoudings wat gebruik word om « model vir « klein oop ekonomie saam te stel. Die tweede deel oorweeg die eienskappe van Suid Afrikaanse makroekonomiese data wat relevant is vir « ekonometriese model in hierdie konteks. Dit sluit « bespreking in van die veranderlikes wat vir so « model gebruik kan word, asook « bespreking van die verskeie metodes wat gebruik kan word om die besigheidsiklus uit die data te identi seer. Die steekproefgrootte van die data word dan vasgestel, ná die moontlikheid van strukturele onderbrekings van tendens in die eerste en tweede momente van die data ondersoek is met behulp van verskeie enkel en meervoudige-veranderlike tegnieke. Die laaste hoofstuk van dié deel is « studie van verskeie maatstawwe van kern in asie (core in ation), waar « vergelyking getref word tussen die resultate van die volgende metodes toegepas op Suid Afrikaanse data: afgesnede gemiddeldes (trimmed means), dinamiese faktor modelle en verskeie golfvormige onderverdelings (wavelet decompositions). Die derde deel gebruik die datastel, wat in deel twee ontwikkel is, in die passing van « DSGE model wat die tipiese eienskappe van « klein oop ekonomie inkorporeer. Dit sluit « bespreking in van die rol van die wisselkoers in hierdie tipe modelle, en daar word empiries bevind dat die wisselkoers belangrike inligting bevat. Hierdie deel sluit ook « ondersoek in van optimale beleid in terme van die reaksie funksie van die sentrale bank. Die laaste deel van die proefskrif bestudeer die resultate van onlangse ontwikkellinge in DSGE modelle wat toegepas word op die Suid Afrikaanse ekonomie. Dit sluit « voorbeeld van « nie-liniêre model wat met behulp van « partikel lter (particle lter) geskat word en gebruik word vir vooruitskattings. Die vooruitskattings uit beide die liniêre en nie-liniêre modelle word dan vergelyk met dié verkry uit verskeie Vektor
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Cremers, Maria L. A. G. "Dynamic and stochastic planing problems with online decision making a novel class of models /." Groningen : [Groningen : University of Groningen ; University Library of Groningen] [Host], 2009. http://irs.ub.rug.nl/ppn/317.
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Jung, Yong-Gook. "Essays on the specification of New Keynesian dynamic stochastic general equilibrium model." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2007. http://wwwlib.umi.com/cr/ucsd/fullcit?p3273810.
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Thesis (Ph. D.)--University of California, San Diego, 2007.Title from first page of PDF file (viewed October 3, 2007). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 60-64).
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Indlekofer, Natalie [Verfasser]. "Methods for Diagnosis and Interpretation of Stochastic Actor-oriented Models for Dynamic Networks / Natalie Indlekofer." Konstanz : Bibliothek der Universität Konstanz, 2014. http://d-nb.info/1049892860/34.
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Elliott, Jennifer T. "Territorial defense and mate attraction in isolated and social white-breasted nuthatches (Sitta carolinensis): tests of stochastic dynamic programming models /." Connect to this title online, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu.
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Thesis (Ph. D.)--Ohio State University, 2005.Title from first page of PDF file. Document formatted into pages; contains xxi, 200 p.; also includes graphics. Includes bibliographical references (p. 194-200). Available online via OhioLINK's ETD Center.
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Ranganathan, Shyam. "Non-linear dynamic modelling for panel data in the social sciences." Doctoral thesis, Uppsala universitet, Tillämpad matematik och statistik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-261289.
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Non-linearities and dynamic interactions between state variables are characteristic of complex social systems and processes. In this thesis, we present a new methodology to model these non-linearities and interactions from the large panel datasets available for some of these systems. We build macro-level statistical models that can verify theoretical predictions, and use polynomial basis functions so that each term in the model represents a specific mechanism. This bridges the existing gap between macro-level theories supported by statistical models and micro-level mechanistic models supported by behavioural evidence. We apply this methodology to two important problems in the social sciences, the demographic transition and the transition to democracy. The demographic transition is an important problem for economists and development scientists. Research has shown that economic growth reduces mortality and fertility rates, which reduction in turn results in faster economic growth. We build a non-linear dynamic model and show how this data-driven model extends existing mechanistic models. We also show policy applications for our models, especially in setting development targets for the Millennium Development Goals or the Sustainable Development Goals. The transition to democracy is an important problem for political scientists and sociologists. Research has shown that economic growth and overall human development transforms socio-cultural values and drives political institutions towards democracy. We model the interactions between the state variables and find that changes in institutional freedoms precedes changes in socio-cultural values. We show applications of our models in studying development traps. This thesis comprises the comprehensive summary and seven papers. Papers I and II describe two similar but complementary methodologies to build non-linear dynamic models from panel datasets. Papers III and IV deal with the demographic transition and policy applications. Papers V and VI describe the transition to democracy and applications. Paper VII describes an application to sustainable development.
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Turhan, Nezihe. "Deterministic and Stochastic Bellman's Optimality Principles on Isolated Time Domains and Their Applications in Finance." TopSCHOLAR®, 2011. http://digitalcommons.wku.edu/theses/1045.
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The concept of dynamic programming was originally used in late 1949, mostly during the 1950s, by Richard Bellman to describe decision making problems. By 1952, he refined this to the modern meaning, referring specifically to nesting smaller decision problems inside larger decisions. Also, the Bellman equation, one of the basic concepts in dynamic programming, is named after him. Dynamic programming has become an important argument which was used in various fields; such as, economics, finance, bioinformatics, aerospace, information theory, etc. Since Richard Bellman's invention of dynamic programming, economists and mathematicians have formulated and solved a huge variety of sequential decision making problems both in deterministic and stochastic cases; either finite or infinite time horizon. This thesis is comprised of five chapters where the major objective is to study both deterministic and stochastic dynamic programming models in finance. In the first chapter, we give a brief history of dynamic programming and we introduce the essentials of theory. Unlike economists, who have analyzed the dynamic programming on discrete, that is, periodic and continuous time domains, we claim that trading is not a reasonably periodic or continuous act. Therefore, it is more accurate to demonstrate the dynamic programming on non-periodic time domains. In the second chapter we introduce time scales calculus. Moreover, since it is more realistic to analyze a decision maker’s behavior without risk aversion, we give basics of Stochastic Calculus in this chapter. After we introduce the necessary background, in the third chapter we construct the deterministic dynamic sequence problem on isolated time scales. Then we derive the corresponding Bellman equation for the sequence problem. We analyze the relation between solutions of the sequence problem and the Bellman equation through the principle of optimality. We give an example of the deterministic model in finance with all details of calculations by using guessing method, and we prove uniqueness and existence of the solution by using the Contraction Mapping Theorem. In the fourth chapter, we define the stochastic dynamic sequence problem on isolated time scales. Then we derive the corresponding stochastic Bellman equation. As in the deterministic case, we give an example in finance with the distributions of solutions.
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Estalrich-Lopez, Juan. "Short-term operation of surface reservoirs within long-term goals." Diss., The University of Arizona, 1989. http://hdl.handle.net/10150/184854.
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A stochastic dynamic programming model (called P.B.S.D.P.) based on the consideration of peak discharge and time between peaks as two stochastic variables has been used to model and to solve a reservoir operation problem. This conceptualization of the physical reality allows to solve, in this order, the tactical and strategic operation of surface reservoirs. This P.B.S.D.P. model has been applied to the Sau reservoir in the Northeastern corner of Spain. The results showed a significant improvement over the currently used operation procedure, yielding values of yearly average electricity production that are somewhat under 6% of what could have been the maximum electricity production.
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Scharrer, Christian [Verfasser], and Burkhard [Akademischer Betreuer] Heer. "Three Essays about Dynamic Stochastic General Equilibrium Models with Overlapping Generations / Christian Scharrer ; Betreuer: Burkhard Heer." Augsburg : Universität Augsburg, 2019. http://d-nb.info/1196529868/34.
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Lu, Lu S. M. Massachusetts Institute of Technology. "W-SPSA : an Efficient Stochastic Approximation Algorithm for the off-line calibration of Dynamic Traffic Assignment models." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/88395.
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Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, February 2014.Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 105-111).
The off-line calibration is a crucial step for the successful application of Dynamic Traffic Assignment (DTA) models in transportation planning and real time traffic management. While traditional approaches focus on the separate or sequential estimation of demand and supply in a DTA system, a recently proposed framework calibrates the demand and supply models simultaneously by formulating the off-line calibration as a constrained optimization problem. Simultaneous Perturbation Stochastic Approximation (SPSA) has been reported in the literature to be the most suitable solution algorithm for this problem due to its highly efficient gradient estimation approach. However, it turns out that the performance of SPSA in terms of convergence rate and long run accuracy can deteriorate significantly when the physical network size and the number of considered time intervals increase. To overcome this problem, this thesis proposes a new algorithm, called Weighted SPSA, or W-SPSA. W-SPSA improves SPSA's gradient estimation process by effectively reducing the noise generated by irrelevant measurements. Synthetic tests are performed to systematically compare the performance of SPSA and W-SPSA. W-SPSA shows scalability and robustness in the tests and outperforms SPSA under different problem scales and characteristics. The application of W-SPSA in real world large-scale DTA systems is demonstrated with a case study of the entire Singapore expressway network. Results show that WSPSA is a more suitable algorithm than SPSA for the off-line calibration of large-scale DTA models. The contributions of the thesis include: 1) identifying limitations of a state-of-the- art solution algorithm for the DTA off-line calibration problem, 2) presenting rigorous definitions of an enhanced algorithm and proposing approaches to estimate the required algorithm parameters, 3) systematically comparing the performance of the new algorithm against the state-of-the-art, 4) demonstrating the characteristics of the new algorithm through experiments, and 5) discussing the general steps and empirical technical considerations when tackling real world DTA off-line calibration problems.
S.M. in Transportation
S.M.
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Schaefer, Stefan [Verfasser]. "Incomplete Information in Dynamic Stochastic General Equilibrium Models : Unvollständige Informationen in dynamischen stochastischen allgemeinen Gleichgewichtsmodellen / Stefan Schaefer." Hamburg : Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2019. http://d-nb.info/1221720953/34.
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Chevallier, Juliette. "Statistical models and stochastic algorithms for the analysis of longitudinal Riemanian manifold valued data with multiple dynamic." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLX059/document.
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Par delà les études transversales, étudier l'évolution temporelle de phénomènes connait un intérêt croissant. En effet, pour comprendre un phénomène, il semble plus adapté de comparer l'évolution des marqueurs de celui-ci au cours du temps plutôt que ceux-ci à un stade donné. Le suivi de maladies neuro-dégénératives s'effectue par exemple par le suivi de scores cognitifs au cours du temps. C'est également le cas pour le suivi de chimiothérapie : plus que par l'aspect ou le volume des tumeurs, les oncologues jugent que le traitement engagé est efficace dès lors qu'il induit une diminution du volume tumoral.L'étude de données longitudinales n'est pas cantonnée aux applications médicales et s'avère fructueuse dans des cadres d'applications variés tels que la vision par ordinateur, la détection automatique d'émotions sur un visage, les sciences sociales, etc.Les modèles à effets mixtes ont prouvé leur efficacité dans l'étude des données longitudinales, notamment dans le cadre d'applications médicales. Des travaux récent (Schiratti et al., 2015, 2017) ont permis l'étude de données complexes, telles que des données anatomiques. L'idée sous-jacente est de modéliser la progression temporelle d'un phénomène par des trajectoires continues dans un espace de mesures, que l'on suppose être une variété riemannienne. Sont alors estimées conjointement une trajectoire moyenne représentative de l'évolution globale de la population, à l'échelle macroscopique, et la variabilité inter-individuelle. Cependant, ces travaux supposent une progression unidirectionnelle et échouent à décrire des situations telles que la sclérose en plaques ou le suivi de chimiothérapie. En effet, pour ces pathologies, vont se succéder des phases de progression, de stabilisation et de remision de la maladie, induisant un changement de la dynamique d'évolution globale.Le but de cette thèse est de développer des outils méthodologiques et algorithmiques pour l’analyse de données longitudinales, dans le cas de phénomènes dont la dynamique d'évolution est multiple et d'appliquer ces nouveaux outils pour le suivi de chimiothérapie. Nous proposons un modèle non-linéaire à effets mixtes dans lequel les trajectoires d'évolution individuelles sont vues comme des déformations spatio-temporelles d'une trajectoire géodésique par morceaux et représentative de l'évolution de la population. Nous présentons ce modèle sous des hypothèses très génériques afin d'englober une grande classe de modèles plus spécifiques.L'estimation des paramètres du modèle géométrique est réalisée par un estimateur du maximum a posteriori dont nous démontrons l'existence et la consistance sous des hypothèses standards. Numériquement, du fait de la non-linéarité de notre modèle, l'estimation est réalisée par une approximation stochastique de l'algorithme EM, couplée à une méthode de Monte-Carlo par chaînes de Markov (MCMC-SAEM). La convergence du SAEM vers les maxima locaux de la vraisemblance observée ainsi que son efficacité numérique ont été démontrées. En dépit de cette performance, l'algorithme SAEM est très sensible à ses conditions initiales. Afin de palier ce problème, nous proposons une nouvelle classe d'algorithmes SAEM dont nous démontrons la convergence vers des minima locaux. Cette classe repose sur la simulation par une loi approchée de la vraie loi conditionnelle dans l'étape de simulation. Enfin, en se basant sur des techniques de recuit simulé, nous proposons une version tempérée de l'algorithme SAEM afin de favoriser sa convergence vers des minima globauxBeyond transversal studies, temporal evolution of phenomena is a field of growing interest. For the purpose of understanding a phenomenon, it appears more suitable to compare the evolution of its markers over time than to do so at a given stage. The follow-up of neurodegenerative disorders is carried out via the monitoring of cognitive scores over time. The same applies for chemotherapy monitoring: rather than tumors aspect or size, oncologists asses that a given treatment is efficient from the moment it results in a decrease of tumor volume. The study of longitudinal data is not restricted to medical applications and proves successful in various fields of application such as computer vision, automatic detection of facial emotions, social sciences, etc.Mixed effects models have proved their efficiency in the study of longitudinal data sets, especially for medical purposes. Recent works (Schiratti et al., 2015, 2017) allowed the study of complex data, such as anatomical data. The underlying idea is to model the temporal progression of a given phenomenon by continuous trajectories in a space of measurements, which is assumed to be a Riemannian manifold. Then, both a group-representative trajectory and inter-individual variability are estimated. However, these works assume an unidirectional dynamic and fail to encompass situations like multiple sclerosis or chemotherapy monitoring. Indeed, such diseases follow a chronic course, with phases of worsening, stabilization and improvement, inducing changes in the global dynamic.The thesis is devoted to the development of methodological tools and algorithms suited for the analysis of longitudinal data arising from phenomena that undergo multiple dynamics and to apply them to chemotherapy monitoring. We propose a nonlinear mixed effects model which allows to estimate a representative piecewise-geodesic trajectory of the global progression and together with spacial and temporal inter-individual variability. Particular attention is paid to estimation of the correlation between the different phases of the evolution. This model provides a generic and coherent framework for studying longitudinal manifold-valued data.Estimation is formulated as a well-defined maximum a posteriori problem which we prove to be consistent under mild assumptions. Numerically, due to the non-linearity of the proposed model, the estimation of the parameters is performed through a stochastic version of the EM algorithm, namely the Markov chain Monte-Carlo stochastic approximation EM (MCMC-SAEM). The convergence of the SAEM algorithm toward local maxima of the observed likelihood has been proved and its numerical efficiency has been demonstrated. However, despite appealing features, the limit position of this algorithm can strongly depend on its starting position. To cope with this issue, we propose a new version of the SAEM in which we do not sample from the exact distribution in the expectation phase of the procedure. We first prove the convergence of this algorithm toward local maxima of the observed likelihood. Then, with the thought of the simulated annealing, we propose an instantiation of this general procedure to favor convergence toward global maxima: the tempering-SAEM
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Saint-Guillain, Michael. "Models and algorithms for online stochastic vehicle routing problems." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEI068.
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Quels seront les objectifs et défis des métropoles de demain ? La plupart des problèmes issus du monde réel sont sujets à l'inconnu, nécessitant de prendre de nouvelles décisions de façon dynamique, à la demande, en fonction des évènements aléatoires qui se réalisent. Dans cette thèse, nous nous attaquons à un problème majeur, du moins en perspectives: la gestion dynamique d'une flotte de véhicules en contexte urbain. Les applications pratiques des tournées de véhicules à la demande sont nombreuses, incluant les transports publics intelligents, les services de livraison, les soins et interventions à domicile, etc. Étant donnés une flotte de véhicules et un ensemble de clients, chacun pouvant potentiellement et à tout moment émettre une requête nécessitant une intervention, l'objectif de cette thèse est de fournir une réponse à la question suivante. Étant donné l'état courant à un moment donné, comment gérer notre flotte de véhicules afin de maximiser l'espérance du nombre total de requêtes satisfaites à la fin de la journée ? Ou encore, comment minimiser l'espérance du délai moyen d'intervention de nos véhicules ? Bien entendu, la difficulté réside en ce que la plupart des requêtes, avant d'apparaître dynamiquement, ne sont pas connues. Pour chaque problème, nous considérons qu'il nous est fourni une connaissance, sous forme d'information probabiliste, telle que la probabilité qu'une requête apparaisse à un certain endroit, et à un certain moment de la journée. Grâce à des techniques issues de la recherche opérationnelle et de la programmation stochastique, nous sommes en mesure de construire et résoudre des modèles calculant les actions anticipatives les plus adéquates, comme le redéploiement préventif des véhicules, minimisant le coût total espéré, ou encore maximisant la qualité de service. La question de l'optimisation sous incertitude se pose depuis déjà plusieurs décennies. Grâce aux avancées à la fois théoriques et technologiques, nous sommes chaque jour un peu plus en mesure de palier à l'inconnu. Cependant, la plupart des problèmes intéressants restent extrêmement difficiles à résoudre, si ce n'est impossible. Il reste beaucoup à faire. Cette thèse explore certains concepts fondamentaux de l'optimisation sous incertitude. En intégrant une composante stochastique aux modèles à optimiser, nous verrons ensemble comment il est en effet possible de créer de l'anticipationWhat will be tomorrow's big cities objectives and challenges? Most of the operational problems from the real world are inherently subject to uncertainty, requiring the decision system to compute new decisions dynamically, as random events occur. In this thesis, we aim at tackling an important growing problem in urban context: online dynamic vehicle routing. Applications of online vehicle routing in the society are manyfold, from intelligent on demand public transportation to sameday delivery services and responsive home healthcare. Given a fleet of vehicles and a set of customers, each being potentially able to request a service at any moment, the current thesis aims at answering the following question. Provided the current state at some moment of the day, which are the best vehicle actions such that the expected number of satisfied requests is maximized by the end of the operational day? How can we minimize the expected average intervention delays of our mobile units? Naturally, most of the requests remain unknown until they appear, hence being revealed online. We assume a stochastic knowledge on each operational problem we tackle, such as the probability that customer request arise at a given location and a given time of the day. By using techniques from operations research and stochastic programming, we are able to build and solve mathematical models that compute near-optimal anticipative actions, such as preventive vehicle relocations, in order to either minimize the overall expected costs or maximize the quality of service. Optimization under uncertainty is definitely not a recent issue. Thanks to evolution of both theoretical and technological tools, our ability to face the unknown constantly grows. However, most of the interesting problems remain extremely hard, if not impossible, to solve. There is still a lot of work. Generally speaking, this thesis explores some fundamentals of optimization under uncertainty. By integrating a stochastic component into the models to be optimized, we will see how it is in fact possible to create anticipation
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Huang, Shih-Yun. "Real investment and dividend policy in a dynamic stochastic general equilibrium (DSGE) model : corporate finance at an aggregate level through DSGE models." Thesis, University of Bradford, 2010. http://hdl.handle.net/10454/5440.
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In this thesis, I take a theoretical dynamic stochastic general equilibrium (DSGE) approach to investigate optimal aggregate dividend policy. I make the following contribution: 1. I extend the standard DSGE model to incorporate a residual dividend policy, external financing and default and find that simulated optimal aggregate payouts are much more volatile than the observed data when other variables are close to the values observed in the data. 2. I examine the sensitivity of optimal aggregate dividend policy to the level of the representative agent's habit motive. My results show that, when the habit motive gets stronger, the volatility of optimal aggregate payouts increases while the volatility of aggregate consumption decreases. This is consistent with the hypothesis that investors use cash payouts from well diversified portfolios to help smooth consumption. 3. I demonstrate that the variability of optimal aggregate payouts is sensitive to capital adjustment costs. My simulated results show that costly frictions from changing the capital base of the firm cause optimal aggregate dividends and real investments to be smooth and share prices to be volatile. This finding is consistent with prior empirical observations. 4. I run simulations that support the hypothesis that optimal aggregate dividend policy is similar when the representative firm is risk averse to when it has capital adjustment costs. In both cases, optimal aggregate dividends volatility is very low. 5. In all calibrated DSGE models, apart from case 4, optimal aggregate payouts are found to be countercyclical. This supports the hypothesis that corporations prefer to hold more free cash flows for potential investment opportunities instead of paying dividends when the economy is booming, but is inconsistent with observed data. Keywords: Dynamic Stochastic General Equilibrium (DSGE), real business cycle, utility function, habits, dividends.
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Liu, Guangling. "Forecasting with DSGE models : the case of South Africa." Thesis, University of Pretoria, 2008. http://hdl.handle.net/2263/25396.
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The objective of this thesis is to develop alternative forms of Dynamic Stochastic General Equilibrium (DSGE) models for forecasting the South African economy and, in turn, compare them with the forecasts generated by the Classical and Bayesian variants of the Vector Autoregression Models (VARs). Such a comparative analysis is aimed at developing a small-scale micro-founded framework that will help in forecasting the key macroeconomic variables of the economy. The thesis consists of three independent papers. The first paper develops a small-scale DSGE model based on Hansen's (1985) indivisible labor Real Business Cycle (RBC) model. The results suggest that, compared to the VARs and the Bayesian VARs, the DSGE model produces large out-of-sample forecast errors. In the basic RBC framework, business cycle fluctuations are purely driven by real technology shocks. This one-shock assumption makes the RBC models stochastically singular. In order to overcome the singularity problem in the RBC model developed in the first paper, the second paper develops a hybrid model (DSGE-VAR), in which the theoretical model is augmented with unobservable errors having a VAR representation. The model is estimated via maximum likelihood technique. The results suggest DSGE-VAR model outperforms the Classical VAR, but not the Bayesian VARs. However, it does indicate that the forecast accuracy can be improved alarmingly by using the estimated version of the DSGE model. The third paper develops a micro-founded New-Keynesian DSGE (NKDSGE) model. The model consists of three equations, an expectational IS curve, a forward-looking version of the Phillips curve, and a Taylor-type monetary policy rule. The results indicate that, besides the usual usage for policy analysis, a small-scale NKDSGE model has a future for forecasting. The NKDSGE model outperforms both the Classical and Bayesian variants of the VARs in forecasting inflation, but not for output growth and the nominal short-term interest rate. However, the differences of the forecast errors are minor. The indicated success of the NKDSGE model for predicting inflation is important, especially in the context of South Africa - an economy targeting inflation.Thesis (PhD (Economics))--University of Pretoria, 2008.
Economics
unrestricted
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Schlosser, Rainer [Verfasser], Kurt [Akademischer Betreuer] Helmes, and Michael C. [Akademischer Betreuer] Burda. "Six essays on stochastic and deterministic dynamic pricing and advertising models / Rainer Schlosser. Gutachter: Kurt Helmes ; Michael C. Burda." Berlin : Humboldt Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät, 2014. http://d-nb.info/1052060617/34.
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Järnberg, Emelie. "Dynamic Credit Models : An analysis using Monte Carlo methods and variance reduction techniques." Thesis, KTH, Matematisk statistik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-197322.
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In this thesis, the credit worthiness of a company is modelled using a stochastic process. Two credit models are considered; Merton's model, which models the value of a firm's assets using geometric Brownian motion, and the distance to default model, which is driven by a two factor jump diffusion process. The probability of default and the default time are simulated using Monte Carlo and the number of scenarios needed to obtain convergence in the simulations is investigated. The simulations are performed using the probability matrix method (PMM), which means that a transition probability matrix describing the process is created and used for the simulations. Besides this, two variance reduction techniques are investigated; importance sampling and antithetic variates.I den här uppsatsen modelleras kreditvärdigheten hos ett företag med hjälp av en stokastisk process. Två kreditmodeller betraktas; Merton's modell, som modellerar värdet av ett företags tillgångar med geometrisk Brownsk rörelse, och "distance to default", som drivs av en två-dimensionell stokastisk process med både diffusion och hopp. Sannolikheten för konkurs och den förväntade tidpunkten för konkurs simuleras med hjälp av Monte Carlo och antalet scenarion som behövs för konvergens i simuleringarna undersöks. Vid simuleringen används metoden "probability matrix method", där en övergångssannolikhetsmatris som beskriver processen används. Dessutom undersöks två metoder för variansreducering; viktad simulering (importance sampling) och antitetiska variabler (antithetic variates).
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Elliott, Jennifer Theresa. "Territorial defense and mate attraction in isolated and social white-breasted nuthatches (Sitta carolinensis): tests of stochastic dynamic programming models." The Ohio State University, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=osu1110207825.
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Souriau, Rémi. "machine learning for modeling dynamic stochastic systems : application to adaptive control on deep-brain stimulation." Electronic Thesis or Diss., université Paris-Saclay, 2021. http://www.theses.fr/2021UPASG004.
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Ces dernières années ont été marquées par l'émergence d'un grand nombre de base données dans de nombreux domaines comme la médecine par exemple. La création de ces bases données a ouvert la voie à de nouvelles applications. Les propriétés des données sont parfois complexes (non linéarité, dynamique, grande dimension ou encore absence d'étiquette) et nécessite des modèles d'apprentissage performants. Parmi les modèles d'apprentissage existant, les réseaux de neurones artificiels ont connu un large succès ces dernières décennies. Le succès de ces modèles repose sur la non linéarité des neurones, l'utilisation de variables latentes et leur grande flexibilité leur permettant de s'adapter à de nombreux problèmes. Les machines de Boltzmann présentées dans cette thèse sont une famille de réseaux de neurones non supervisés. Introduite par Hinton dans les années 80, cette famille de modèle a connu un grand intérêt dans le début du 21e siècle et de nouvelles extensions sont proposées régulièrement.Cette thèse est découpée en deux parties. Une partie exploratoire sur la famille des machines de Boltzmann et une partie applicative. L'application étudiée est l'apprentissage non supervisé des signaux électroencéphalogramme intracrânien chez les rats Parkinsonien pour le contrôle des symptômes de la maladie de Parkinson.Les machines de Boltzmann ont donné naissance aux réseaux de diffusion. Il s'agit de modèles non supervisés qui reposent sur l'apprentissage d'une équation différentielle stochastique pour des données dynamiques et stochastiques. Ce réseau fait l'objet d'un développement particulier dans cette thèse et un nouvel algorithme d'apprentissage est proposé. Son utilisation est ensuite testée sur des données jouet ainsi que sur des données réellesThe past recent years have been marked by the emergence of a large amount of database in many fields like health. The creation of many databases paves the way to new applications. Properties of data are sometimes complex (non linearity, dynamic, high dimensions) and require to perform machine learning models. Belong existing machine learning models, artificial neural network got a large success since the last decades. The success of these models lies on the non linearity behavior of neurons, the use of latent units and the flexibility of these models to adapt to many different problems. Boltzmann machines presented in this thesis are a family of generative neural networks. Introduced by Hinton in the 80's, this family have got a large interest at the beginning of the 21st century and new extensions are regularly proposed.This thesis is divided into two parts. A first part exploring Boltzmann machines and their applications. In this thesis the unsupervised learning of intracranial electroencephalogram signals on rats with Parkinson's disease for the control of the symptoms is studied.Boltzmann machines gave birth to Diffusion networks which are also generative model based on the learning of a stochastic differential equation for dynamic and stochastic data. This model is studied again in this thesis and a new training algorithm is proposed. Its use is tested on toy data as well as on real database
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Zhu, Liyu. "Discrete Brand Choice Models: Analysis and Applications." Diss., Available online, Georgia Institute of Technology, 2007, 2007. http://etd.gatech.edu/theses/available/etd-07102007-142035/.
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Thesis (Ph. D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2008.Esogbue, Augustine, Committee Chair ; Griffin, Paul, Committee Member ; Lu, Jye-Chyi (JC), Committee Member ; Li, MinQiang, Committee Member ; McCarthy, Patrick, Committee Member.
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Arastuie, Makan. "Generative Models of Link Formation and Community Detection in Continuous-Time Dynamic Networks." University of Toledo / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1596718772873086.
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