Relevant bibliographies by topics / Multivariate utility

Academic literature on the topic 'Multivariate utility'

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Published: 9 March 2023
Last updated: 10 March 2023

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Journal articles on the topic "Multivariate utility"

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Scarsini, Marco. "Dominance Conditions for Multivariate Utility Functions." Management Science 34, no. 4 (April 1988): 454–60. http://dx.doi.org/10.1287/mnsc.34.4.454.

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Charpentier, Arthur, Alfred Galichon, and Marc Henry. "Local Utility and Multivariate Risk Aversion." Mathematics of Operations Research 41, no. 2 (May 2016): 466–76. http://dx.doi.org/10.1287/moor.2015.0736.

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Aichinger, Florian, and Sascha Desmettre. "Utility Maximization in Multivariate Volterra Models." SIAM Journal on Financial Mathematics 14, no. 1 (January 19, 2023): 52–98. http://dx.doi.org/10.1137/21m1464543.

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Dyckerhoff, Rainer. "Decomposition of multivariate utility functions in non-additive expected utility theory." Journal of Multi-Criteria Decision Analysis 3, no. 1 (April 1994): 41–58. http://dx.doi.org/10.1002/mcda.4020030106.

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Safra, Zvi, and Uzi Segal. "Dominance Axioms and Multivariate Nonexpected Utility Preferences." International Economic Review 34, no. 2 (May 1993): 321. http://dx.doi.org/10.2307/2526915.

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Campi, Luciano, and Mark P. Owen. "Multivariate utility maximization with proportional transaction costs." Finance and Stochastics 15, no. 3 (April 20, 2010): 461–99. http://dx.doi.org/10.1007/s00780-010-0125-9.

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Kritzman, Mark, and Don R. Rich. "Risk Containment for Investors with Multivariate Utility Functions." Journal of Derivatives 5, no. 3 (February 28, 1998): 28–44. http://dx.doi.org/10.3905/jod.1998.407996.

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Escobar-Anel, Marcos. "Multivariate risk aversion utility, application to ESG investments." North American Journal of Economics and Finance 63 (November 2022): 101790. http://dx.doi.org/10.1016/j.najef.2022.101790.

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Karni, Edi. "Generalized Expected Utility Analysis of Multivariate Risk Aversion." International Economic Review 30, no. 2 (May 1989): 297. http://dx.doi.org/10.2307/2526648.

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Li, Mingli, Xiaojing Li, Deng Wei, Yinfei Li, Liansheng Zhao, Xiaohong Ma, Yingcheng Wang, et al. "S179. PROGNOSTIC UTILITY OF MULTIVARIATE MORPHOMETRY IN SCHIZOPHRENIA." Schizophrenia Bulletin 44, suppl_1 (April 1, 2018): S394. http://dx.doi.org/10.1093/schbul/sby018.966.

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Dissertations / Theses on the topic "Multivariate utility"

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LOREGIAN, ANGELA. "Multivariate Lèvy models: estimation and asset allocation." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/49727.

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Multidimensional asset models based on Lévy processes have been introduced to meet the necessity of capturing market shocks using more refined distribution assumptions compared to the standard Gaussian framework. In particular, along with accurately modeling marginal distributions of asset returns, capturing the dependence structure among them is of paramount importance, for example, to correctly price derivatives written on more than one underlying asset. Most of the literature on multivariate Lévy models focuses in fact on pricing multi-asset products, which is also the case of the model introduced in Ballotta and Bonfiglioli (2014). Believing that risk and portfolio management applications may benefit from a better description of the joint distribution of the returns as well, we choose to adopt Ballotta and Bonfiglioli (2014) model for asset allocation purposes and we empirically test its performances. We choose this model since, besides its flexibility and the ability to properly capture the dependence among assets, it is simple, relatively parsimonious and it has an immediate and intuitive interpretation, retaining a high degree of mathematical tractability. In particular we test two specifications of the general model, assuming respectively a pure jump process, more precisely the normal inverse Gaussian process, or a jump-diffusion process, precisely Merton’s jump-diffusion process, for all the components involved in the model construction. To estimate the model we propose a simple and easy-to-implement three-step procedure, which we assess via simulations, comparing the results with those obtained through a more computationally intensive one-step maximum likelihood estimation. We empirically test portfolio construction based on multivariate Lévy models assuming a standard utility maximization framework; for the exponential utility function we get a closed form expression for the expected utility, while for other utility functions (we choose to test the power one) we resort to numerical approximations. Among the benchmark strategies, we consider in our study what we call a ‘non-parametric optimization approach’, based on Gaussian kernel estimation of the portfolio return distribution, which to our knowledge has never been used. A different approach to allocation decisions aims at minimizing portfolio riskiness requiring a minimum expected return. Following Rockafellar and Uryasev (2000), we describe how to solve this optimization problem in our multivariate Lévy framework, when risk is measured by CVaR. Moreover we present formulas and methods to compute, as efficiently as possible, some downside risk measures for portfolios made of assets following the multivariate Lévy model by Ballotta and Bonfiglioli (2014). More precisely, we consider traditional risk measures (VaR and CVaR), the corresponding marginal measures, which evaluate their sensibility to portfolio weights alterations, and intra-horizon risk measures, which take into account the magnitude of losses that can incur before the end of the investment horizon. Formulas for CVaR in monetary terms and marginal measures, together with our approach to evaluate intra-horizon risk, are among the original contributions of this work.
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Collart, Philippe. "Impact à court terme de la pollution atmosphérique sur la santé en Wallonie :utilité d’une approche multivariable." Doctoral thesis, Universite Libre de Bruxelles, 2017. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/253702.

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De nombreuses études ont mis en évidence les effets à court terme entre la pollution atmosphérique et l’état de santé. Les principaux polluants de l’air sont les particules en suspension, le dioxyde d’azote, l’ozone et le dioxyde de soufre. Ils sont produits essentiellement par le trafic routier et les industries. La température est également associée à la santé cardiovasculaire ou respiratoire et elle peut aussi avoir un effet modificateur sur l’association entre la pollution atmosphérique et événements sanitaires. Les effets à court terme de la pollution atmosphérique peuvent être immédiats, décalés ou cumulés. Le décalage entre exposition et effet sanitaire peut être d’un à plusieurs jours. En général, on observe des effets immédiats pour les maladies cardiovasculaires et des effets légèrement décalés pour les maladies respiratoires. Les maladies cardiovasculaires sont la première cause de mortalité dans les pays industrialisés. Les facteurs de risque de ces maladies sont liés à la fois à l’environnement, aux comportements et aux caractéristiques génétiques des individus. Une association entre pollution atmosphérique, principalement les particules en suspension et le NO2, et morbi-mortalité a été mise en évidence pour les maladies cardiovasculaires suivantes :les accidents vasculaires cérébraux (AVC), les troubles du rythme et l’infarctus du myocarde (IDM). Le but de cette thèse est d’évaluer l’impact à court terme de la pollution atmosphérique sur la santé cardiovasculaire ainsi que sur la mortalité non traumatique en Wallonie et en Belgique tout en vérifiant si des effets immédiats, décalés ou cumulés peuvent être observés en fonction des sensibilités différentielles des sujets exposés.
Doctorat en Santé Publique
info:eu-repo/semantics/nonPublished
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DOLDI, ALESSANDRO. "EQUILIBRIUM, SYSTEMIC RISK MEASURES AND OPTIMAL TRANSPORT: A CONVEX DUALITY APPROACH." Doctoral thesis, Università degli Studi di Milano, 2021. http://hdl.handle.net/2434/812668.

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This Thesis focuses on two main topics. Firstly, we introduce and analyze the novel concept of Systemic Optimal Risk Transfer Equilibrium (SORTE), and we progressively generalize it (i) to a multivariate setup and (ii) to a dynamic (conditional) setting. Additionally we investigate its relation to a recently introduced concept of Systemic Risk Measures (SRM). We present Conditional Systemic Risk Measures and study their properties, dual representation and possible interpretations of the associated allocations as equilibria in the sense of SORTE. On a parallel line of work, we develop a duality for the Entropy Martingale Optimal Transport problem and provide applications to problems of nonlinear pricing-hedging. The mathematical techniques we exploit are mainly borrowed from functional and convex analysis, as well as probability theory. More specifically, apart from a wide range of classical results from functional analysis, we extensively rely on Fenchel-Moreau-Rockafellar type conjugacy results, Minimax Theorems, theory of Orlicz spaces, compactness results in the spirit of Komlós Theorem. At the same time, mathematical results concerning utility maximization theory (existence of optima for primal and dual problems, just to mention an example) and optimal transport theory are widely exploited. The notion of SORTE is inspired by the Bühlmann's classical Equilibrium Risk Exchange (H. Bühlmann, "The general economic premium principle", Astin Bulletin, 1984). In both the Bühlmann and the SORTE definition, each agent is behaving rationally by maximizing his/her expected utility given a budget constraint. The two approaches differ by the budget constraints. In Bühlmann's definition the vector that assigns the budget constraint is given a priori. In the SORTE approach, on the contrary, the budget constraint is endogenously determined by solving a systemic utility maximization problem. SORTE gives priority to the systemic aspects of the problem, in order to first optimize the overall systemic performance, rather than to individual rationality. Single agents' preferences are, however, taken into account by the presence of individual optimization problems. The two aspects are simultaneously considered via an optimization problem for a value function given by summation of single agents' utilities. After providing a financial and theoretical justification for this new idea, in this research sufficient general assumptions that guarantee existence, uniqueness, and Pareto optimality of such a SORTE are presented. Once laid the theoretical foundation for the newly introduced SORTE, this Thesis proceeds in extending such a notion to the case when the value function to be optimized has two components, one being the sum of the single agents' utility functions, as in the aforementioned case of SORTE, the other consisting of a truly systemic component. This marks the progress from SORTE to Multivariate Systemic Optimal Risk Transfer Equilibrium (mSORTE). Technically, the extension of SORTE to the new setup requires developing a theory for multivariate utility functions and selecting at the same time a suitable framework for the duality theory. Conceptually, this more general setting allows us to introduce and study a Nash Equilibrium property of the optimizers. Existence, uniqueness, Pareto optimality and the Nash Equilibrium property of the newly defined mSORTE are proved in this Thesis. Additionally, it is shown how mSORTE is in fact a proper generalization, and covers both from the conceptual and the mathematical point of view the notion of SORTE. Proceeding further in the analysis, the relations between the concepts of mSORTE and SRM are investigated in this work. The notion of SRM we start from was introduced in the papers "A unified approach to systemic risk measures via acceptance sets" (Math. Finance, 2019) and "On fairness of systemic risk measures" (Finance Stoch., 2020) by F. Biagini, J.-P. Fouque, M. Frittelli, and T. Meyer-Brandis. SRM of Biagini et al. are generalized in this Thesis to a dynamic (namely conditional) setting, adding also a systemic, multivariate term in the threshold functions that Biagini et al. consider in their papers. The dynamic version of mSORTE is introduced, and it is proved that the optimal allocations of dynamic SRM, together with the corresponding fair pricing measures, yield a dynamic mSORTE. This in particular remains true if conditioning is taken with respect to the trivial sigma algebra, which is tantamount to working in the non-dynamic setting covered in Biagini et al. for SRM, and in the previous parts of our work for mSORTE. The case of exponential utility functions is thoroughly examined, and the explicit formulas we obtain for this specific choice of threshold functions allow for providing a time consistency property for allocations, dynamic SRM and dynamic mSORTE. The last part of this Thesis is devoted to a conceptually separate topic. Nonetheless, a clear mathematical link between the previous work and the one we are to describe is established by the use of common techniques. A duality between a novel Entropy Martingale Optimal Transport (EMOT) problem (D) and an associated optimization problem (P) is developed. In (D) the approach taken in Liero et al. (M. Liero, A. Mielke, and G. Savaré, "Optimal entropy-transport problems and a new Hellinger-Kantorovich distance between positive measures", Inventiones mathematicae, 2018) serves as a basis for adding the constraint, typical of Martingale Optimal Transport (MOT) theory, that the infimum of the cost functional is taken over martingale probability measures, instead of finite positive measures, as in Liero et al.. The Problem (D) differs from the corresponding problem in Liero et al. not only by the martingale constraint, but also because we admit less restrictive penalization terms D, which may not have a divergence formulation. In Problem (P) the objective functional, associated via Fenchel conjugacy to the terms D, is not any more linear, as in Optimal Transport or in MOT. This leads to a novel optimization problem which also has a clear financial interpretation as a non linear subhedging value. Our results in this Thesis establish a novel nonlinear robust pricing-hedging duality in financial mathematics, which covers a wide range of known robust results in its generality. The research for this Thesis resulted in the production of the following works: F. Biagini, A. Doldi, J.-P. Fouque, M. Frittelli, and T. Meyer-Brandis, "Systemic optimal risk transfer equilibrium", Mathematics and Financial Economics, 2021; A. Doldi and M. Frittelli, "Multivariate Systemic Optimal Risk Transfer Equilibrium", Preprint: arXiv:1912.12226, 2019; A. Doldi and M. Frittelli, "Conditional Systemic Risk Measures", Preprint: arXiv:2010.11515, 2020; A. Doldi and M. Frittelli, "Entropy Martingale Optimal Transport and Nonlinear Pricing-Hedging Duality", Preprint: arXiv:2005.12572, 2020.
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Lima, Maria Santana Bezerra de. "Utiliza??o da espectroscopia no infravermelho pr?ximo para o controle de qualidade do camar?o (Litopenaeus vannamei)." Universidade Federal do Rio Grande do Norte, 2015. http://repositorio.ufrn.br/handle/123456789/20383.

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Este trabalho foi desenvolvido com o objetivo de propor uma rotina metodol?gica simples, r?pida e vers?til utilizando espectroscopia de infravermelho pr?ximo (NIR) aliada ? an?lise multivariada para a determina??o dos teores de cinzas, umidade, prote?na e lip?dios totais presentes no camar?o cinza (Litopenaeus vannamei) que convencionalmente ? realizada por gravimetria ap?s redu??o a cinzas a 550 oC por gravimetria ap?s secagem em estufa a 105 ?C para a determina??o de umidade, gravimetria ap?s extra??o utilizando Soxhlet e volumetria ap?s digest?o e destila??o por Kjedhal, respectivamente. Inicialmente, foram coletados os espectros de 63 amostras processadas de camar?o cozidos da esp?cie Litopenaeus vannamei. Em seguida, foram realizadas as determina??es pelos m?todos convencionais de refer?ncia. Os espectros centrados na m?dia foram submetidos ? corre??o de espalhamento multiplicativo da luz, alisamento de Saviztky-Golay em 15 pontos e primeira derivada, eliminada a regi?o ruidosa, a faixa de trabalho foi 1036,15 a 3232,49 nm. Desta forma, os modelos PLS para predi??o de cinzas mostraram R 0,9419, RMSEC 0,1065 e RMSEP 0,1929; para umidade o R foi de 0,7704, RMSEC 4,1407 e RMSEP 4,6948; para prote?na R 0,8510, RMSEC 2,6372 e RMSEP 2,8468; para lip?dios R 0,8078, RMSEC 0,3618 e RMSEP 0,2255 De maneira que, os resultados mostraram que os erros relativos encontrados entre o m?todo de refer?ncia e o NIR foram pequenos e satisfat?rios. Estes resultados s?o um excelente indicativo de que se pode utilizar o NIR para estas an?lises, o que ? bastante vantajoso, j? que as t?cnicas convencionais s?o demoradas, gastam uma grande quantidade de reagentes e envolvem v?rios profissionais, o que demanda um tempo razo?vel de execu??o, enquanto que ap?s a valida??o da metodologia a execu??o utilizando NIR reduz todo esse tempo para alguns minutos, com economia de reagentes, de tempo e sem gera??o de res?duos, al?m de tratar-se de uma t?cnica n?o destrutiva.
This work was developed with the objective of proposing a simple, fast and versatile methodological routine using near-infrared spectroscopy (NIR) combined with multivariate analysis for the determination of ash content, moisture, protein and total lipids present in the gray shrimp (Litopenaeus vannamei ) which is conventionally performed gravimetrically after ashing at 550 ? C gravimetrically after drying at 105 ? C for the determination of moisture gravimetrically after a Soxhlet extraction using volumetric and after digestion and distillation Kjedhal respectively. Was first collected the spectra of 63 samples processed boiled shrimp Litopenaeus vannamei species. Then, the determinations by conventional standard methods were carried out. The spectra centered average underwent multiplicative scattering correction of light, smoothing Saviztky-Golay 15 points and first derivative, eliminated the noisy region, the working range was from 1100,36 to 2502,37 nm. Thus, the PLS models for predicting ash showed R 0,9471; 0,1017 and RMSEP RMSEC 0,1548; Moisture R was 0,9241; 2,5483 and RMSEP RMSEC 4,1979; R protein to 0,9201; 1,9391 and RMSEP RMSEC 2,7066; for lipids R 0,8801; 0,2827 and RMSEP RMSEC 0,2329 So that the results showed that the relative errors found between the reference method and the NIR were small and satisfactory. These results are an excellent indication that you can use the NIR to these analyzes, which is quite advantageous, since conventional techniques are time consuming, they spend a lot of reagents and involve a number of professionals, which requires a reasonable runtime while after the validation of the methodology execution using NIR reduces all this time to a few minutes, saving reagents, time and without waste generation, and that this is a non-destructive technique.
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Assareh, Hassan. "Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals." Thesis, Queensland University of Technology, 2012. https://eprints.qut.edu.au/53342/1/Hassan_Assareh_Thesis.pdf.

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Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.
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Books on the topic "Multivariate utility"

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Safra, Zvi. Dominance axioms and multivariate nonexpected utility preferences. Toronto: Dept. of Economics and Institute for Policy Analysis, University of Toronto, 1990.

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Weirich, Paul. Decision Space: Multidimensional Utility Analysis (Cambridge Studies in Probability, Induction and Decision Theory). Cambridge University Press, 2001.

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Decision Space: Multidimensional Utility Analysis (Cambridge Studies in Probability, Induction and Decision Theory). Cambridge University Press, 2007.

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Gelfand, Alan, and Sujit K. Sahu. Models for demography of plant populations. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.17.

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This article discusses the use of Bayesian analysis and methods to analyse the demography of plant populations, and more specifically to estimate the demographic rates of trees and how they respond to environmental variation. It examines data from individual (tree) measurements over an eighteen-year period, including diameter, crown area, maturation status, and survival, and from seed traps, which provide indirect information on fecundity. The multiple data sets are synthesized with a process model where each individual is represented by a multivariate state-space submodel for both continuous (fecundity potential, growth rate, mortality risk, maturation probability) and discrete states (maturation status). The results from plant population demography analysis demonstrate the utility of hierarchical modelling as a mechanism for the synthesis of complex information and interactions.
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Ramírez Chung, José Francisco, Herman Bernardo Collazos Saldaña, Nadia Masaya Panduro Tenazoa, and Noé Ramírez Flores. Factores agroeconómicos y su relación con la subutilización en tres cultivos nativos de la comunidad flor de castaña Río Ucayali – Sapuena - Perú. Universidad Nacional Autónoma de Tayacaja Daniel Hernández Morillo (UNAT) - Fondo Editorial., 2022. http://dx.doi.org/10.56224/ediunat.14.

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Esta investigación se desarrolló en la selva baja del Perú, en la región de Loreto, provincia de Requena, distrito de Sapuena, comunidad de Flor de Castaña – Río Ucayali, cuyo objetivo fue determinar la relación entre factores agroeconómicos y la subutilización en tres cultivos como son la sacha papa (Dioscorea trífida), pituca (Colocasia esculenta) y witina (Xanthosoma sagittifolium) durante el año 2016. El estudio fue una investigación cuantitativa, del nivel relacional, no experimental, transversal, relacionando las variables de asociación y de supervisión (relacional simple). Para la conformación de la muestra se utilizó el método censal con criterios de inclusión y exclusión. De acuerdo a los resultados del análisis estadístico se encontró para los factores agronómicos que la opinión mayoritaria de los agricultores fue que son cultivos de periodos vegetativos largos o medianos, des uniformes en la maduración y cosecha, con periodos de post cosecha medianos, con problemas de plagas, rápido deterioro después de la cosecha, y demora en la cocción. En cuanto a factores económicos, la opinión mayoritaria fue que dichos cultivos cuentan con vías de transporte inadecuadas y con baja rentabilidad, y con factores de subutilización expresadas en bajas áreas de siembra, baja producción y escasa presencia en el mercado. Solo algunas variables agronómicas y económicas se pueden utilizar como predictores de la subutilización y dependiendo del cultivo pero que en todos los casos y de acuerdo al valor del estadístico en la prueba de hipótesis de asociación Tau b Kendall dichas variables no son muy determinantes de la asociación, existiendo probablemente otros factores o variables con mayor determinación del mismo, lo cual conlleva a realizar estudios posteriores utilizando el análisis multivariado.
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Book chapters on the topic "Multivariate utility"

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Koning, Ruud H., and Geert Ridder. "Utility Maximisation and Mode of Payment." In Innovations in Multivariate Statistical Analysis, 117–36. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4603-0_8.

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Dyckerhoff, Rainer. "Decomposition of Multivariate Utility Functions in Non-Additive Expected Utility Theory." In Operations Research ’91, 467–70. Heidelberg: Physica-Verlag HD, 1992. http://dx.doi.org/10.1007/978-3-642-48417-9_129.

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Huntley, John Warren. "Exploratory Multivariate Techniques and Their Utility for Understanding Ancient Ecosystems." In Topics in Geobiology, 23–48. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0680-4_2.

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Tang, Jingye, Tianqing Zhu, Ping Xiong, Yu Wang, and Wei Ren. "Privacy and Utility Trade-Off for Textual Analysis via Calibrated Multivariate Perturbations." In Network and System Security, 342–53. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65745-1_20.

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Okada, Taketo, Farit Mochamad Afendi, Akira Katoh, Aki Hirai, and Shigehiko Kanaya. "Multivariate Analysis of Analytical Chemistry Data and Utility of the KNApSAcK Family Database to Understand Metabolic Diversity in Medicinal Plants." In Biotechnology for Medicinal Plants, 413–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29974-2_18.

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Abbadi, A., and F.Hamidia. "Multivariable Extremum Seeking MPPT Control for Photovoltaic Farm Connected to Utility Grid." In Artificial Intelligence and Heuristics for Smart Energy Efficiency in Smart Cities, 237–44. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-92038-8_24.

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Mathai, Arak M., Serge B. Provost, and Hans J. Haubold. "The Distributions of Eigenvalues and Eigenvectors." In Multivariate Statistical Analysis in the Real and Complex Domains, 549–96. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95864-0_8.

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AbstractWe will utilize the same notations as in the previous chapters. Lower-case letters x, y, … will denote real scalar variables, whether mathematical or random. Capital letters X, Y, … will be used to denote real matrix-variate mathematical or random variables, whether square or rectangular matrices are involved. A tilde will be placed on top of letters such as $$\tilde {x},\tilde {y},\tilde {X},\tilde {Y}$$ x ~ , y ~ , X ~ , Y ~ to denote variables in the complex domain. Constant matrices will for instance be denoted by A, B, C. A tilde will not be used on constant matrices unless the point is to be stressed that the matrix is in the complex domain. Other notations will remain unchanged.
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Mathai, Arak M., Serge B. Provost, and Hans J. Haubold. "Profile Analysis and Growth Curves." In Multivariate Statistical Analysis in the Real and Complex Domains, 813–44. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95864-0_14.

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AbstractWe will utilize the same notations as in the previous chapters. Lower-case letters x, y, … will denote real scalar variables, whether mathematical or random. Capital letters X, Y, … will be used to denote real matrix-variate mathematical or random variables, whether square or rectangular matrices are involved. A tilde will be placed on top of letters such as $$\tilde {x},\tilde {y},\tilde {X},\tilde {Y}$$ x ~ , y ~ , X ~ , Y ~ to denote variables in the complex domain. Constant matrices will for instance be denoted by A, B, C. A tilde will not be used on constant matrices unless the point is to be stressed that the matrix is in the complex domain.
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Mathai, Arak M., Serge B. Provost, and Hans J. Haubold. "Factor Analysis." In Multivariate Statistical Analysis in the Real and Complex Domains, 679–710. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95864-0_11.

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AbstractWe will utilize the same notations as in the previous chapters. Lower-case letters x, y, … will denote real scalar variables, whether mathematical or random. Capital letters X, Y, … will be used to denote real matrix-variate mathematical or random variables, whether square or rectangular matrices are involved. A tilde will be placed on top of letters such as $$\tilde {x},\tilde {y},\tilde {X},\tilde {Y}$$ x ~ , y ~ , X ~ , Y ~ to denote variables in the complex domain. Constant matrices will for instance be denoted by A, B, C. A tilde will not be used on constant matrices unless the point is to be stressed that the matrix is in the complex domain.
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Passantino, Andrea, Pietro Guida, Giuseppe Parisi, Massimo Iacoviello, and Domenico Scrutinio. "Critical Appraisal of Multivariable Prognostic Scores in Heart Failure: Development, Validation and Clinical Utility." In Advances in Experimental Medicine and Biology, 387–403. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/5584_2017_135.

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Conference papers on the topic "Multivariate utility"

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Kamizono, Kenji. "Multivariate Utility Maximization under Transaction Costs." In Proceedings of the Ritsumeikan International Symposium. WORLD SCIENTIFIC, 2004. http://dx.doi.org/10.1142/9789812702852_0007.

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Feyisetan, Oluwaseyi, Borja Balle, Thomas Drake, and Tom Diethe. "Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations." In WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3336191.3371856.

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Chen, Xi, Ali E. Abbas, and Dusˇan M. Stipanovic´. "A Multiattribute Utility Approach to Target Assignment." In ASME 2009 Dynamic Systems and Control Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/dscc2009-2594.

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This paper introduces the multiattribute utility theory to the control Lyapunov function design framework. As an illustration we focus on the problem of multi-target assignment. With this formulation, we use a global multiattribute utility function as a multivariate objective function that should be minimized for the agents to achieve their objectives. The objectives represent deviations of each agent from specified targets. We provide closed form feedback control laws, based on the multiattribute utility function, for general nonlinear multi-agent system models affine in control. Finally, we present simulation results and conduct sensitivity analysis for two different models that are affine in control; basic kinematic model and nonlinear nonholonomic unicycle model.
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Zhou, Feng, and Jianxin (Roger) Jiao. "A Nested Multivariate Utility Copulas Approach to Aggregating User Experience Partworths for Aircraft Cabin Interior Design." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-13691.

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User experience (UX) design involves combination of different design attributes with their corresponding attribute levels to form different product profiles. This raises the issue of how to integrate corresponding UX of individual design attribute levels (i.e., partworth UX measures) into a holistic measure of UX of the entire product profile. Traditional methods often use a weighted sum of single partworth UX strategy without considering their dependence. This paper proposes to use utility copulas to accommodate the dependence of individual partworth UX measures. Single utility functions are constructed based on cumulative prospect theory, based on which multivariate Archimedean utility copulas are constructed using a nested structure based on the modularized attributes. A case study of aircraft cabin interior design is demonstrated to show the potential and feasibility of the proposed methodology.
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Zhong, Ming, Jared Schuetter, Srikanta Mishra, and Randy F. LaFollette. "Do Data Mining Methods Matter? : A Wolfcamp “Shale” Case Study." In SPE Hydraulic Fracturing Technology Conference. SPE, 2015. http://dx.doi.org/10.2118/spe-173334-ms.

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Abstract Data mining for production optimization in unconventional reservoirs brings together data from multiple sources with varying levels of aggregation, detail, and quality. Tens of variables are typically included in data sets to be analyzed. There are many statistical and machine learning techniques that can be used to analyze data and summarize the results. These methods were developed to work extremely well in certain scenarios but can be terrible choices in others. The analyst may or may not be trained and experienced in using those methods. The question for both the analyst and the consumer of data mining analyses is, “What difference does the method make in the final interpreted result of an analysis?” The objective of this study was to compare and review the relative utility of several univariate and multivariate statistical and machine learning methods in predicting the production quality of Permian Basin Wolfcamp Shale wells. The data set for the study was restricted to wells completed in and producing from the Wolfcamp. Data categories used in the study included the well location and assorted metrics capturing various aspects of the well architecture, well completion, stimulation, and production. All of this information was publicly available. Data variables were scrutinized and corrected for inconsistent units and were sanity checked for out-of-bounds and other “bad data” problems. After the quality control effort was completed, the test data set was distributed among the statistical team for application of an agreed upon set of statistical and machine learning methods. Methods included standard univariate and multivariate linear regression as well as advanced machine learning techniques such as Support Vector Machine, Random Forests, and Boosted Regression Trees. The strengths, limitations, implementation, and study results of each of the methods tested are discussed and compared to those of the other methods. Consistent with other data mining studies, univariate linear methods are shown to be much less robust than multivariate non-linear methods, which tend to produce more reliable results. The practical importance is that when tens to hundreds of millions of dollars are at stake in the development of shale reservoirs, operators should have the confidence that their decisions are statistically sound. The work presented here shows that methods do matter, and useful insights can be derived regarding complex geosystem behavior by geoscientists, engineers, and statisticians working together.
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Muralidhar, Nikhil, Sathappan Muthiah, and Naren Ramakrishnan. "DyAt Nets: Dynamic Attention Networks for State Forecasting in Cyber-Physical Systems." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/441.

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Multivariate time series forecasting is an important task in state forecasting for cyber-physical systems (CPS). State forecasting in CPS is imperative for optimal planning of system energy utility and understanding normal operational characteristics of the system thus enabling anomaly detection. Forecasting models can also be used to identify sub-optimal or worn out components and are thereby useful for overall system monitoring. Most existing work only performs single step forecasting but in CPS it is imperative to forecast the next sequence of system states (i.e curve forecasting). In this paper, we propose DyAt (Dynamic Attention) networks, a novel deep learning sequence to sequence (Seq2Seq) model with a novel hierarchical attention mechanism for long-term time series state forecasting. We evaluate our method on several CPS state forecasting and electric load forecasting tasks and find that our proposed DyAt models yield a performance improvement of at least 13.69% for the CPS state forecasting task and a performance improvement of at least 18.83% for the electric load forecasting task over other state-of-the-art forecasting baselines. We perform rigorous experimentation with several variants of the DyAt model and demonstrate that the DyAt models indeed learn better representations over the entire course of the long term forecast as compared to their counterparts with or without traditional attention mechanisms. All data and source code has been made available online.
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Alkhalaqi, Aysha, Fatima Alnaimi, Rouda Qassmi, and Hiba Bawadi. "Predictive Power of Body Visceral Adiposity Index, Body Adiposity Index and Body Mass Index for Type 2 Diabetes in Qatari Population." In Qatar University Annual Research Forum & Exhibition. Qatar University Press, 2020. http://dx.doi.org/10.29117/quarfe.2020.0208.

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Background: The prevalence of type 2 diabetes (T2D) has increased recently in Qatar. Body mass index (BMI) is a predictor of T2D in many populations. However, BMI is based on height and weight measurements and not on body adiposity. Therefore, the utility of BMI for predicting the risk of T2D has been questioned, and visceral adiposity (VAI) appears to be a better predictor of T2D. Objective: This study is aimed to assess the relative effectiveness of visceral adiposity index (VAI) and body adiposity index (BAI), in comparison with body mass index (BMI), for T2D among Qatari adults. Methodology: A random sample of 1103 adult Qatari nationals over 20 years old were included in this study; this data was obtained from the Qatar National Biobank. We performed a multivariate logistic regression to examine the association between VAI, BAI, BMI, and T2D, and computed zscores for VAI, BAI and BMI. Results: VAI z-scores showed the strongest association with the risk of T2D (OR, 1.44; 95% CI: 1.24–1.68) compared with the zscores for BAI (OR, 1.15; 95% CI: 0.93–1.43) and BMI (OR, 1.33; 95% CI: 1.11–1.59). Subgroup analyses indicated that the association was stronger between VAI and T2D in Qatari women than in men. Conclusion: VAI was a strong and independent predictor of T2D among the Qatari adult population. Therefore, VAI could be a useful tool for predicting the risk of T2D among Qatari adults.
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AlMukdad, Sawsan Ibrahim, Hazem Elewa, and Daoud Al-Badriyeh. "Economic Evaluation of CYP2C19 Genotype-Guided Antiplatelet Therapy Compared to Universal use of Ticagrelor or Clopidogrel in Qatar." In Qatar University Annual Research Forum & Exhibition. Qatar University Press, 2020. http://dx.doi.org/10.29117/quarfe.2020.0170.

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Background: Patients having CYP2C19 loss-of-function alleles and receiving clopidogrel are at higher risk of adverse cardiovascular outcomes. Ticagrelor is a more effective and expensive antiplatelet that is unaffected by the CYP2C19 polymorphism. The main aim of the current research is to evaluate the cost-effectiveness among CYP2C19 genotype-guided therapy, universal ticagrelor, and universal clopidogrel after a percutaneous coronary intervention (PCI). Methods: A two-part simulation model, including a one-year decision-analytic model and a 20-year followup Markov model, was created to follow the use of (i) universal clopidogrel, (ii) universal ticagrelor, and (iii) genotype-guided antiplatelet therapy. Outcome measures were the incremental cost-effectiveness ratio (ICER, cost/success) and incremental cost-utility ratio (ICUR, cost/qualityadjusted life years [QALY]). Therapy success was defined as survival without myocardial infarction, stroke, cardiovascular death, stent thrombosis, and no therapy discontinuation because of adverse events, i.e. major bleeding and dyspnea. The model was based on a multivariate analysis, and a sensitivity analysis confirmed the robustness of the model outcomes. Results: Against universal clopidogrel, genotype-guided therapy was cost-effective over the one-year duration (ICER, USD 6,102 /success), and dominant over the long-term. Genotype-guided therapy was dominant over universal ticagrelor over the one-year duration and cost-effective over the long term (ICUR, USD 1,383 /QALY). Universal clopidogrel was dominant over ticagrelor over the short term, and cost-effective over the long-term (ICUR, 10,616 /QALY). Conclusion: CYP2C19 genotype-guided therapy appears to be the preferred antiplatelet strategy, followed by universal clopidogrel, and then universal ticagrelor for post-PCI patients in Qatar.
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Cristescu, Irina, and Alexandru Balog. "HETEROGENEITY OF STUDENTS' PERCEPTIONS OF E-LEARNING PLATFORM QUALITY: A LATENT PROFILE ANALYSIS." In eLSE 2019. Carol I National Defence University Publishing House, 2019. http://dx.doi.org/10.12753/2066-026x-19-097.

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E-learning platform quality is an important subject in the community of researchers and practitioners. Quality assessment approaches have different perspectives and differ in many respects, such as: objective, target groups and methods used. In recent years, the utility of advanced person-centered methods has become increasingly obvious. Person-centered approaches assume that samples come from heterogeneous populations and focus on identifying unobservable subpopulations that include individuals or similar cases. In this category are included both traditional techniques (e.g. cluster analysis) and advanced techniques (e.g. Latent Class Analysis, Latent Profile Analysis). In the present study, the e-learning platform quality is a general concept defined through three dimensions. The overall perception of students regarding the e-learning platform quality is based on the assessment of the following dimensions: e-learning system quality, information quality, and service quality. The aim of this paper is to extend previous research by adopting a person-oriented approach (e.g. LPA - latent profile analysis) and examine the heterogeneity of students' perceptions of e-learning platform quality. A sample of 385 students from five Romanian universities participated in the study. The data was analyzed with Mplus package version 7.4. The results of LPA revealed the presence of three profiles, reflecting different levels of e-learning platform quality perceptions: low, moderate, and high. The resulting profiles are distinct with respect to e-learning system quality, information quality, and service quality. A one-way multivariate analysis of variance (MANOVA) showed that the perceptions of e-learning platforms quality differed significantly across the three profiles. Finally, the article presented the practical implications of the results. The results contribute, on one hand, to identifying groups of students who shared similar perception patterns when dealing with e-learning platform quality. On the other hand, the results are useful in developing a strategy of improving the e-learning platforms by including the specific needs of each student categories identified.
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Assaf, Roy, and Anika Schumann. "Explainable Deep Neural Networks for Multivariate Time Series Predictions." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/932.

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We demonstrate that CNN deep neural networks can not only be used for making predictions based on multivariate time series data, but also for explaining these predictions. This is important for a number of applications where predictions are the basis for decisions and actions. Hence, confidence in the prediction result is crucial. We design a two stage convolutional neural network architecture which uses particular kernel sizes. This allows us to utilise gradient based techniques for generating saliency maps for both the time dimension and the features. These are then used for explaining which features during which time interval are responsible for a given prediction, as well as explaining during which time intervals was the joint contribution of all features most important for that prediction. We demonstrate our approach for predicting the average energy production of photovoltaic power plants and for explaining these predictions.
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