Relevant bibliographies by topics / Modelling, Markov chain

Academic literature on the topic 'Modelling, Markov chain'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Modelling, Markov chain.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Modelling, Markov chain"

1

BOUCHER, THOMAS R., and DAREN B. H. CLINE. "PIGGYBACKING THRESHOLD PROCESSES WITH A FINITE STATE MARKOV CHAIN." Stochastics and Dynamics 09, no. 02 (June 2009): 187–204. http://dx.doi.org/10.1142/s0219493709002622.

Full text
Abstract:
The state-space representations of certain nonlinear autoregressive time series are general state Markov chains. The transitions of a general state Markov chain among regions in its state-space can be modeled with the transitions among states of a finite state Markov chain. Stability of the time series is then informed by the stationary distributions of the finite state Markov chain. This approach generalizes some previous results.
APA, Harvard, Vancouver, ISO, and other styles
2

Gerontidis, Ioannis I. "Semi-Markov Replacement Chains." Advances in Applied Probability 26, no. 03 (September 1994): 728–55. http://dx.doi.org/10.1017/s0001867800026525.

Full text
Abstract:
We consider an absorbing semi-Markov chain for which each time absorption occurs there is a resetting of the chain according to some initial (replacement) distribution. The new process is a semi-Markov replacement chain and we study its properties in terms of those of the imbedded Markov replacement chain. A time-dependent version of the model is also defined and analysed asymptotically for two types of environmental behaviour, i.e. either convergent or cyclic. The results contribute to the control theory of semi-Markov chains and extend in a natural manner a wide variety of applied probability models. An application to the modelling of populations with semi-Markovian replacements is also presented.
APA, Harvard, Vancouver, ISO, and other styles
3

Gerontidis, Ioannis I. "Semi-Markov Replacement Chains." Advances in Applied Probability 26, no. 3 (September 1994): 728–55. http://dx.doi.org/10.2307/1427818.

Full text
Abstract:
We consider an absorbing semi-Markov chain for which each time absorption occurs there is a resetting of the chain according to some initial (replacement) distribution. The new process is a semi-Markov replacement chain and we study its properties in terms of those of the imbedded Markov replacement chain. A time-dependent version of the model is also defined and analysed asymptotically for two types of environmental behaviour, i.e. either convergent or cyclic. The results contribute to the control theory of semi-Markov chains and extend in a natural manner a wide variety of applied probability models. An application to the modelling of populations with semi-Markovian replacements is also presented.
APA, Harvard, Vancouver, ISO, and other styles
4

Faddy, M. J., and S. I. McClean. "Markov Chain Modelling for Geriatric Patient Care." Methods of Information in Medicine 44, no. 03 (2005): 369–73. http://dx.doi.org/10.1055/s-0038-1633979.

Full text
Abstract:
Summary Objectives: To show that Markov chain modelling can be applied to data on geriatric patients and use these models to assess the effects of covariates. Methods: Phase-type distributions were fitted by maximum likelihood to data on times spent by the patients in hospital and in community-based care. Data on the different events that ended the patients’ periods of care were used to estimate the dependence of the probabilities of these events on the phase from which the time in care ended. The age of the patients at admission to care and the year of admission were also included as covariates. Results: Differential effects of these covariates were shown on the various parameters of the fitted model, and interpretations of these effects made. Conclusions: Models based on phase-type distributions were appropriate for describing times spent in care, as the ordered phases had an interpretable structure corresponding to increasing amounts of care being given.
APA, Harvard, Vancouver, ISO, and other styles
5

SINGHAL, EKTA, and Kunal Mehta. "Marketing Channel Attribution Modelling: Markov Chain Analysis." International Journal of Indian Culture and Business Management 1, no. 1 (2020): 1. http://dx.doi.org/10.1504/ijicbm.2020.10027991.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Mehta, Kunal, and Ekta Singhal. "Marketing channel attribution modelling: Markov chain analysis." International Journal of Indian Culture and Business Management 21, no. 1 (2020): 63. http://dx.doi.org/10.1504/ijicbm.2020.109344.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Hadjinicola, George, and Larry Goldstein. "Markov chain modelling of bioassay toxicity procedures." Statistics in Medicine 12, no. 7 (April 15, 1993): 661–74. http://dx.doi.org/10.1002/sim.4780120705.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Catak, Muammer, Nurşin Baş, Kevin Cronin, Dario Tellez-Medina, Edmond P. Byrne, and John J. Fitzpatrick. "Markov chain modelling of fluidised bed granulation." Chemical Engineering Journal 164, no. 2-3 (November 1, 2010): 403–9. http://dx.doi.org/10.1016/j.cej.2010.02.022.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Huang, Vincent, and James Unwin. "Markov chain models of refugee migration data." IMA Journal of Applied Mathematics 85, no. 6 (September 29, 2020): 892–912. http://dx.doi.org/10.1093/imamat/hxaa032.

Full text
Abstract:
Abstract The application of Markov chains to modelling refugee crises is explored, focusing on local migration of individuals at the level of cities and days. As an explicit example, we apply the Markov chains migration model developed here to United Nations High Commissioner for Refugees data on the Burundi refugee crisis. We compare our method to a state-of-the-art ‘agent-based’ model of Burundi refugee movements, and highlight that Markov chain approaches presented here can improve the match to data while simultaneously being more algorithmically efficient.
APA, Harvard, Vancouver, ISO, and other styles
10

Balzter, Heiko. "Markov chain models for vegetation dynamics." Ecological Modelling 126, no. 2-3 (February 2000): 139–54. http://dx.doi.org/10.1016/s0304-3800(00)00262-3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Modelling, Markov chain"

1

Samci, Karadeniz Rukiye. "Modelling share prices as a random walk on a Markov chain." Thesis, University of Leicester, 2017. http://hdl.handle.net/2381/40129.

Full text
Abstract:
In the financial area, a simple but also realistic means of modelling real data is very important. Several approaches are considered to model and analyse the data presented herein. We start by considering a random walk on an additive functional of a discrete time Markov chain perturbed by Gaussian noise as a model for the data as working with a continuous time model is more convenient for option prices. Therefore, we consider the renowned (and open) embedding problem for Markov chains: not every discrete time Markov chain has an underlying continuous time Markov chain. One of the main goals of this research is to analyse whether the discrete time model permits extension or embedding to the continuous time model. In addition, the volatility of share price data is estimated and analysed by the same procedure as for share price processes. This part of the research is an extensive case study on the embedding problem for financial data and its volatility. Another approach to modelling share price data is to consider a random walk on the lamplighter group. Specifically, we model data as a Markov chain with a hidden random walk on the lamplighter group Z3 and on the tensor product of groups Z2 ⊗ Z2. The lamplighter group has a specific structure where the hidden information is actually explicit. We assume that the positions of the lamplighters are known, but we do not know the status of the lamps. This is referred to as a hidden random walk on the lamplighter group. A biased random walk is constructed to fit the data. Monte Carlo simulations are used to find the best fit for smallest trace norm difference of the transition matrices for the tensor product of the original transition matrices from the (appropriately split) data. In addition, splitting data is a key method for both our first and second models. The tensor product structure comes from the split of the data. This requires us to deal with the missing data. We apply a variety of statistical techniques such as Expectation- Maximization Algorithm and Machine Learning Algorithm (C4.5). In this work we also analyse the quantum data and compute option prices for the binomial model via quantum data.
APA, Harvard, Vancouver, ISO, and other styles
2

Gallagher, Raymond. "Uncertainty modelling in quantitative risk analysis." Thesis, University of Liverpool, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.367676.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Pang, Wan-Kai. "Modelling ordinal categorical data : a Gibbs sampler approach." Thesis, University of Southampton, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323876.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Kawale, Sujay J. "Implication of Terrain Topology Modelling on Ground Vehicle Reliability." Thesis, Virginia Tech, 2010. http://hdl.handle.net/10919/31241.

Full text
Abstract:
The accuracy of computer-based ground vehicle durability and ride quality simulations depends on accurate representation of road surface topology as an excitation to vehicle dynamics simulation software, since most of the excitation input to a vehicle as it traverses terrain is provided by the surface topology. It is not computationally efficient to utilise physically measured terrain topology for these simulations since extremely large data sets would be required to represent terrain of all desired types. Moreover, performing repeated simulations on the same set of measured data would not provide a random character typical of real world usage. There exist several methods of synthesising terrain data through the use of stochastic or mathematical models in order to capture such physical properties of measured terrain as roughness, bank angle and grade. In first part of this work, the autoregressive model and the Markov chain model have been applied to generate synthetic two-dimensional terrain profiles. The synthesised terrain profiles generated are expected to capture the statistical properties of the measured data. A methodology is then proposed; to assess the performance of these models of terrain in capturing the statistical properties of the measured terrain. This is done through the application of several statistical property tests to the measured and synthesized terrain profiles. The second part of this work describes the procedure that has been followed to assess the performance of these models in capturing the vehicle component fatigue-inducing characteristics of the measured terrain, by predicting suspension component fatigue life based on the loading conditions obtained from the measured terrain and the corresponding synthesized terrain. The terrain model assessment methodology presented in this work can be applied to any model of terrain, serving to identify which terrain models are suited to which type of terrain.
Master of Science
APA, Harvard, Vancouver, ISO, and other styles
5

Bray, Isabelle Cella. "Modelling the prevalence of Down syndrome with applications of Markov chain Monte Carlo methods." Thesis, University of Plymouth, 1998. http://hdl.handle.net/10026.1/2408.

Full text
Abstract:
This thesis was motivated by applications in the epidemiology of Down syndrome and prenatal screening for Down syndrome. Methodological problems arising in these applications include under-ascertainment of cases in livebirth studies, double-sampled data with missing observations and coarsening of data. These issues are considered from a classical perspective using maximum likelihood and from a Bayesian viewpoint employing Markov chain Monte Carlo (MCMC) techniques. Livebirth prevalence studies published in the literature used a variety of data collection methods and many are of uncertain completeness. In two of the nine studies an estimate of the level of under-reporting is available. We present a meta-analysis of these studies in which maternal age-related risks and the levels of under-ascertainment in individual studies are estimated simultaneously. A modified logistic model is used to describe the relationship between Down syndrome prevalence and maternal age. The model is then extended to include data from several studies of prevalence rates observed at times of chorionic villus sampling (CVS) and amniocentesis. New estimates for spontaneous loss rates between the times" of CVS, amniocentesis and live birth are presented. The classical analysis of live birth prevalence data is then compared with an MCMC analysis which allows prior information concerning ascertainment to be incorporated. This approach is particularly attractive since the double-sampled data structure includes missing observations. The MCMC algorithm, which uses single-component Metropolis-Hastings steps to simulate model parameters and missing data, is run under three alternative prior specifications. Several convergence diagnostics are also considered and compared. Finally, MCMC techniques are used to model the distribution of fetal nuchal translucency (NT), an ultrasound marker for Down syndrome. The data are a mixture of measurements rounded to whole millimetres and measurements more accurately recorded to one decimal place. An MCMC algorithm is applied to simulate the proportion of measurements rounded to whole millimetres and parameters to describe the distribution of NT in unaffected and Down syndrome pregnancies. Predictive probabilities of Down syndrome given NT and maternal age are then calculated.
APA, Harvard, Vancouver, ISO, and other styles
6

Loza, Reyes Elisa. "Classification of phylogenetic data via Bayesian mixture modelling." Thesis, University of Bath, 2010. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.519916.

Full text
Abstract:
Conventional probabilistic models for phylogenetic inference assume that an evolutionary tree,andasinglesetofbranchlengthsandstochasticprocessofDNA evolutionare sufficient to characterise the generating process across an entire DNA alignment. Unfortunately such a simplistic, homogeneous formulation may be a poor description of reality when the data arise from heterogeneous processes. A well-known example is when sites evolve at heterogeneous rates. This thesis is a contribution to the modelling and understanding of heterogeneityin phylogenetic data. Weproposea methodfor the classificationof DNA sites based on Bayesian mixture modelling. Our method not only accounts for heterogeneous data but also identifies the underlying classes and enables their interpretation. We also introduce novel MCMC methodology with the same, or greater, estimation performance than existing algorithms but with lower computational cost. We find that our mixture model can successfully detect evolutionary heterogeneity and demonstrate its direct relevance by applying it to real DNA data. One of these applications is the analysis of sixteen strains of one of the bacterial species that cause Lyme disease. Results from that analysis have helped understanding the evolutionary paths of these bacterial strains and, therefore, the dynamics of the spread of Lyme disease. Our method is discussed in the context of DNA but it may be extendedto othertypesof molecular data. Moreover,the classification scheme thatwe propose is evidence of the breadth of application of mixture modelling and a step forwards in the search for more realistic models of theprocesses that underlie phylogenetic data.
APA, Harvard, Vancouver, ISO, and other styles
7

Garzon, Rozo Betty Johanna. "Modelling operational risk using skew t-copulas and Bayesian inference." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/25751.

Full text
Abstract:
Operational risk losses are heavy tailed and are likely to be asymmetric and extremely dependent among business lines/event types. The analysis of dependence via copula models has been focussed on the bivariate case mainly. In the vast majority of instances symmetric elliptical copulas are employed to model dependence for severities. This thesis proposes a new methodology to assess, in a multivariate way, the asymmetry and extreme dependence between severities, and to calculate the capital for operational risk. This methodology simultaneously uses (i) several parametric distributions and an alternative mixture distribution (the Lognormal for the body of losses and the generalised Pareto Distribution for the tail) using a technique from extreme value theory, (ii) the multivariate skew t-copula applied for the first time across severities and (iii) Bayesian theory. The former to model severities, I test simultaneously several parametric distributions and the mixture distribution for each business line. This procedure enables me to achieve multiple combinations of the severity distribution and to find which fits most closely. The second to effectively model asymmetry and extreme dependence in high dimensions. The third to estimate the copula model, given the high multivariate component (i.e. eight business lines and seven event types) and the incorporation of mixture distributions it is highly difficult to implement maximum likelihood. Therefore, I use a Bayesian inference framework and Markov chain Monte Carlo simulation to evaluate the posterior distribution to estimate and make inferences of the parameters of the skew t-copula model. The research analyses an updated operational loss data set, SAS® Operational Risk Global Data (SAS OpRisk Global Data), to model operational risk at international financial institutions. I then evaluate the impact of this multivariate, asymmetric and extreme dependence on estimating the total regulatory capital, among other established multivariate copulas. My empirical findings are consistent with other studies reporting thin and medium-tailed loss distributions. My approach substantially outperforms symmetric elliptical copulas, demonstrating that modelling dependence via the skew t-copula provides a more efficient allocation of capital charges of up to 56% smaller than that indicated by the standard Basel model.
APA, Harvard, Vancouver, ISO, and other styles
8

Bleki, Zolisa. "Efficient Bayesian analysis of spatial occupancy models." Master's thesis, University of Cape Town, 2020. http://hdl.handle.net/11427/32469.

Full text
Abstract:
Species conservation initiatives play an important role in ecological studies. Occupancy models have been a useful tool for ecologists to make inference about species distribution and occurrence. Bayesian methodology is a popular framework used to model the relationship between species and environmental variables. In this dissertation we develop a Gibbs sampling method using a logit link function in order to model posterior parameters of the single-season spatial occupancy model. We incorporate the widely used Intrinsic Conditional Autoregressive (ICAR) prior model to specify the spatial random effect in our sampler. We also develop OccuSpytial, a statistical package implementing our Gibbs sampler in the Python programming language. The aim of this study is to highlight the computational efficiency that can be obtained by employing several techniques, which include exploiting the sparsity of the precision matrix of the ICAR model and also making use of Polya-Gamma latent variables to obtain closed form expressions for the posterior conditional distributions of the parameters of interest. An algorithm for efficiently sampling from the posterior conditional distribution of the spatial random effects parameter is also developed and presented. To illustrate the sampler's performance a number of simulation experiments are considered, and the results are compared to those obtained by using a Gibbs sampler incorporating Restricted Spatial Regression (RSR) to specify the spatial random effect. Furthermore, we fit our model to the Helmeted guineafowl (Numida meleagris) dataset obtained from the 2nd South African Bird Atlas Project database in order to obtain a distribution map of the species. We compare our results with those obtained from the RSR variant of our sampler, those obtained by using the stocc statistical package (written using the R programming language), and those obtained from not specifying any spatial information about the sites in the data. It was found that using RSR to specify spatial random effects is both statistically and computationally more efficient that specifying them using ICAR. The OccuSpytial implementations of both ICAR and RSR Gibbs samplers has significantly less runtime compared to other implementations it was compared to.
APA, Harvard, Vancouver, ISO, and other styles
9

Henriques, Bruno M. "Hybrid galaxy evolution modelling : Monte Carlo Markov Chain parameter estimation in semi-analytic models of galaxy formation." Thesis, University of Sussex, 2010. http://sro.sussex.ac.uk/id/eprint/2334/.

Full text
Abstract:
We introduce a statistical exploration of the parameter space of the Munich semi-analytic model built upon the Millennium dark matter simulation. This is achieved by applying a Monte Carlo Markov Chain (MCMC) method to constrain the 6 free parameters that define the stellar mass function at redshift zero. The model is tested against three different observational data sets, including the galaxy K-band luminosity function, B −V colours, and the black hole-bulge mass relation, to obtain mean values, confidence limits and likelihood contours for the best fit model. We discuss how the model parameters affect each galaxy property and find that there are strong correlations between them. We analyze to what extent these are simply reflections of the observational constraints, or whether they can lead to improved understanding of the physics of galaxy formation. When all the observations are combined, the need to suppress dwarf galaxies requires the strength of the supernova feedback to be significantly higher in our best-fit solution than in previous work. We interpret this fact as an indication of the need to improve the treatment of low mass objects. As a possible solution, we introduce the process of satellite disruption, caused by tidal forces exerted by central galaxies on their merging companions. We apply similar MCMC sampling techniques to the new model, which allows us to discuss the impact of disruption on the basic physics of the model. The new best fit model has a likelihood four times better than before, reproducing reasonably all the observational constraints, as well as the metallicity of galaxies and predicting intra-cluster light. We interpret this as an indication of the need to include the new recipe. We point out the remaining limitations of the semi-analytic model and discuss possible improvements that might increase its predictive power in the future.
APA, Harvard, Vancouver, ISO, and other styles
10

Dao, Trong Nghia Electrical Engineering &amp Telecommunications Faculty of Engineering UNSW. "Modelling 802.11 networks for multimedia applications." Publisher:University of New South Wales. Electrical Engineering & Telecommunications, 2008. http://handle.unsw.edu.au/1959.4/41222.

Full text
Abstract:
This thesis is concerned with the development of new mathematical models for the IEEE 802.11??s access mechanisms, with a particular focus on DCF and EDCA. Accurate mathematical models for the DCF and EDCA access mechanisms provide many benefits, such as improved performance analysis, easier network capacity planning, and robust network design. A feature that permeates the work presented in this thesis is the application of our new models to network environments where both saturated and non-saturated traffic sources are present. The scenario in which multiple traffic sources are present is more technically challenging, but provides for a more realistic setting. Our first contribution is the development of a new Markov model for non-saturated DCF in order to predict the network throughput. This model takes into account several details of the protocol that have been hitherto neglected. In addition, we apply a novel treatment of the packet service time within our model. We show how the inclusion of these effects provides more accurate predictions of network throughput than earlier works. Our second contribution is the development of a new analytical model for EDCA, again in order to predict network throughput. Our new EDCA model is based on a replacement of the normal AIFS parameter of EDCA with a new parameter more closely associated with DCF. This novel procedure allows EDCA to be viewed as a modified multi-mode version of DCF. Our third contribution is the simultaneous application of our new Markov models to both the non-saturated and the saturated regime. Hitherto, network throughput predictions for these regimes have required completely separate mathematical models. The convergence property of our model in the two regimes provides a new method to estimate the network capacity of the network. Our fourth contribution relates to predictions for the multimedia capacity of 802.11 networks. Our multimedia capacity analysis, which is based on modifications to our Markov model, is new in that it can be applied to a broad range of quality of service requirements. Finally, we highlight the use of our analysis in the context of emerging location-enabled networks.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Modelling, Markov chain"

1

Groen, Maria Margaretha de. Modelling interception and transpiration at monthly time steps: Introducing daily variability through Markov chains. Lisse: Swets & Zeitlinger, 2002.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Winkler, Gerhard. Image Analysis, Random Fields and Markov Chain Monte Carlo Methods: A Mathematical Introduction (Stochastic Modelling and Applied Probability). 2nd ed. Springer, 2006.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Quintana, José Mario, Carlos Carvalho, James Scott, and Thomas Costigliola. Extracting S&P500 and NASDAQ Volatility: The Credit Crisis of 2007–2008. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.13.

Full text
Abstract:
This article demonstrates the utility of Bayesian modelling and inference in financial market volatility analysis, using the 2007-2008 credit crisis as a case study. It first describes the applied problem and goal of the Bayesian analysis before introducing the sequential estimation models. It then discusses the simulation-based methodology for inference, including Markov chain Monte Carlo (MCMC) and particle filtering methods for filtering and parameter learning. In the study, Bayesian sequential model choice techniques are used to estimate volatility and volatility dynamics for daily data for the year 2007 for three market indices: the Standard and Poor’s S&P500, the NASDAQ NDX100 and the financial equity index called XLF. Three models of financial time series are estimated: a model with stochastic volatility, a model with stochastic volatility that also incorporates jumps in volatility, and a Garch model.
APA, Harvard, Vancouver, ISO, and other styles
4

Lopes, Hedibert, and Nicholas Polson. Analysis of economic data with multiscale spatio-temporal models. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.12.

Full text
Abstract:
This article discusses the use of Bayesian multiscale spatio-temporal models for the analysis of economic data. It demonstrates the utility of a general modelling approach for multiscale analysis of spatio-temporal processes with areal data observations in an economic study of agricultural production in the Brazilian state of Espìrito Santo during the period 1990–2005. The article first describes multiscale factorizations for spatial processes before presenting an exploratory multiscale data analysis and explaining the motivation for multiscale spatio-temporal models. It then examines the temporal evolution of the underlying latent multiscale coefficients and goes on to introduce a Bayesian analysis based on the multiscale decomposition of the likelihood function along with Markov chain Monte Carlo (MCMC) methods. The results from agricultural production analysis show that the spatio-temporal framework can effectively analyse massive economics data sets.
APA, Harvard, Vancouver, ISO, and other styles
5

Discrete-Time Markov Chains: Two-Time-Scale Methods and Applications (Stochastic Modelling and Applied Probability). Springer, 2004.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

Zhang, Qing, and George G. Yin. Continuous-Time Markov Chains and Applications: A Singular Perturbation Approach (Stochastic Modelling and Applied Probability). Springer, 1997.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Zhang, Qing, and G. George Yin. Discrete-Time Markov Chains: Two-Time-Scale Methods and Applications (Stochastic Modelling and Applied Probability Book 55). Springer New York, 2006.

Find full text
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Modelling, Markov chain"

1

Asmussen, Søren, and Peter W. Glynn. "Markov Chain Monte Carlo Methods." In Stochastic Modelling and Applied Probability, 350–80. New York, NY: Springer New York, 2007. http://dx.doi.org/10.1007/978-0-387-69033-9_13.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Suman, S. K., and S. Sinha. "Pavement Performance Modelling Using Markov Chain." In Proceedings of the International Symposium on Engineering under Uncertainty: Safety Assessment and Management (ISEUSAM - 2012), 619–27. India: Springer India, 2012. http://dx.doi.org/10.1007/978-81-322-0757-3_39.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Maione, B., M. P. Fanti, and B. Turchiano. "Large Scale Markov Chain Modelling of Transfer Lines." In Operations Research Models in Flexible Manufacturing Systems, 193–211. Vienna: Springer Vienna, 1989. http://dx.doi.org/10.1007/978-3-7091-2654-7_9.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Derouault, Anne-Marie, and Bernard Merialdo. "Language modelling using a hidden Markov chain with application to automatic transcription of French stenotypy." In Semi-Markov Models, 475–85. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4899-0574-1_29.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Petrov, Tatjana. "Markov Chain Aggregation and Its Application to Rule-Based Modelling." In Modeling Biomolecular Site Dynamics, 297–313. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9102-0_14.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Strickland, Christopher M., Robert J. Denham, Clair L. Alston, and Kerrie L. Mengersen. "A Python Package for Bayesian Estimation Using Markov Chain Monte Carlo." In Case Studies in Bayesian Statistical Modelling and Analysis, 421–60. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781118394472.ch25.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Conejo, S., A. Morata, and F. Valero. "First Order Markov Chain Model and Rainfall Sequences in several Stations of Spain." In Detecting and Modelling Regional Climate Change, 417–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04313-4_36.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Balaji Rao, K. "Markov Chain Modelling of Evolution of Deflection in Ferrocement Flexural Members." In Emerging Trends of Advanced Composite Materials in Structural Applications, 67–96. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1688-4_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Chotard, Alexandre, and Martin Holeňa. "A Generalized Markov-Chain Modelling Approach to (1,λ)-ES Linear Optimization." In Parallel Problem Solving from Nature – PPSN XIII, 902–11. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10762-2_89.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Han, Zhonghua, Yuehan Liu, Haibo Shi, and Xutian Tian. "A Dynamic Buffer Reservation Method Based on Markov Chain to Solve Deadlock Problem in Scheduling." In Proceedings of the 11th International Conference on Modelling, Identification and Control (ICMIC2019), 1205–13. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0474-7_113.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Modelling, Markov chain"

1

Waller, Ephraim Nii Kpakpo, Pamela Delali Adablah, and Quist-Aphetsi Kester. "Markov Chain: Forecasting Economic Variables." In 2019 International Conference on Computing, Computational Modelling and Applications (ICCMA). IEEE, 2019. http://dx.doi.org/10.1109/iccma.2019.00026.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Perera, Supun, Michael G. H. Bell, Fumitaka Kurauchi, and Dharshana Kasthurirathna. "Absorbing Markov Chain Approach to Modelling Disruptions in Supply Chain Networks." In 2019 Moratuwa Engineering Research Conference (MERCon). IEEE, 2019. http://dx.doi.org/10.1109/mercon.2019.8818809.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Raj, Akash, and SMAK Azad. "Markov Chain Modelling of Standby Redundant Networked Control System." In 2019 Fifth International Conference on Electrical Energy Systems (ICEES). IEEE, 2019. http://dx.doi.org/10.1109/icees.2019.8719303.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Winkovich, T., and D. Eckardt. "Reliability analysis of safety systems using Markov-chain modelling." In 2005 IEEE 11th European Conference on Power Electronics and Applications. IEEE, 2005. http://dx.doi.org/10.1109/epe.2005.219620.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Mapp, Glenford, Dhawal Thakker, and Orhan Gemikonakli. "Exploring a New Markov Chain Model for Multiqueue Systems." In 2010 12th International Conference on Computer Modelling and Simulation. IEEE, 2010. http://dx.doi.org/10.1109/uksim.2010.113.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Popa, D., and J. Tomasik. "On Markov Chain Modelling of Asynchronous Optical CSMA/CA Protocol." In 2007 15th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS). IEEE, 2007. http://dx.doi.org/10.1109/mascots.2007.44.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Arkov, V. Yu, G. G. Kulikov, and T. V. Breikin. "Application of Markov Chains to Identification of Turbine Engine Dynamic Models." In ASME Turbo Expo 2002: Power for Land, Sea, and Air. ASMEDC, 2002. http://dx.doi.org/10.1115/gt2002-30038.

Full text
Abstract:
The paper addresses the problem of dynamic modelling of gas turbines for condition monitoring purposes. Identification of dynamic models is performed using a novel Markov chain technique. This includes identifiability analysis and model estimation. When identifying the model, experimental data should be sufficiently informative for identification. So far, identifiability analysis is weak formed and workable solutions are still to be developed. A possible technique is proposed based on non-parametric models in the form of controllable Markov chains. The second step in systems identification is the model estimation. At this stage, Markov chains are introduced to provide more functionality and versatility for dynamic modelling of gas turbines. The Markov chain model combines the deterministic and stochastic components of the engine dynamics within a single model, thus providing more exact and adequate description of the real system behaviour and leading to far more accurate health monitoring.
APA, Harvard, Vancouver, ISO, and other styles
8

"Inverse of magnetic dipole field using a reversible jump Markov chain Monte Carlo." In 20th International Congress on Modelling and Simulation (MODSIM2013). Modelling and Simulation Society of Australia and New Zealand, 2013. http://dx.doi.org/10.36334/modsim.2013.a2.luo.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Chan, Ronald, Pengfei Zhang, Wenyu Zhang, Ido Nevat, Alvin Valera, Hwee-Xian Tan, and Natarajan Gautam. "Adaptive duty cycling in sensor networks via Continuous Time Markov Chain modelling." In 2015 IEEE International Conference on Signal Processing for Communications (ICC). IEEE, 2015. http://dx.doi.org/10.1109/icc.2015.7249388.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Datta, Soumendra Nath, Sowjanya Vankayalapati, Atanu Guchhait, Shekar Nethi, Sushanth Gajanan, Yongseok Park, Daekyu Choi, and Sang-Jun Moon. "Finite State Markov Chain modelling of IEEE TGn channels for packet level simulators." In 2014 International Conference on Signal Processing and Communications (SPCOM). IEEE, 2014. http://dx.doi.org/10.1109/spcom.2014.6983980.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Modelling, Markov chain' for particular source types:
Journal articles Dissertations / Theses
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography