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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

A review and application of hidden Markov models and double chain Markov models

Hoff, Michael Ryan January 2016 (has links)
A Dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in ful lment of the requirements for the degree of Master of Science. Johannesburg, 2016. / Hidden Markov models (HMMs) and double chain Markov models (DCMMs) are classical Markov model extensions used in a range of applications in the literature. This dissertation provides a comprehensive review of these models with focus on i) providing detailed mathematical derivations of key results - some of which, at the time of writing, were not found elsewhere in the literature, ii) discussing estimation techniques for unknown model parameters and the hidden state sequence, and iii) discussing considerations which practitioners of these models would typically take into account. Simulation studies are performed to measure statistical properties of estimated model parameters and the estimated hidden state path - derived using the Baum-Welch algorithm (BWA) and the Viterbi Algorithm (VA) respectively. The effectiveness of the BWA and the VA is also compared between the HMM and DCMM. Selected HMM and DCMM applications are reviewed and assessed in light of the conclusions drawn from the simulation study. Attention is given to application in the field of Credit Risk. / LG2017

Estimation of spectral gap using coupling techniques /

Nandy, Rajesh Ranjan. January 2001 (has links)
Thesis (Ph. D.)--University of Washington, 2001. / Vita. Includes bibliographical references (leaves 53-54).

Some results on higher order Markov Chain models /

Kwok, Chi-on, Michael. January 1988 (has links)
Thesis (M. Phil.)--University of Hong Kong, 1989.

Construction of non-standard Markov chain models with applications

Zhu, Dongmei, 朱冬梅 January 2014 (has links)
In this thesis, the properties of some non-standard Markov chain models and their corresponding parameter estimation methods are investigated. Several practical applications and extensions are also discussed. The estimation of model parameters plays a key role in the real-world applications of Markov chain models. Some widely used estimation methods for Markov chain models are based on the existence of stationary vectors. In this thesis, some weaker sufficient conditions for the existence of stationary vectors for highorder Markov chain models, multivariate Markov chain models and high-order multivariate Markov chain models are proposed. Furthermore, for multivariate Markov chain models, a new estimation method based on minimizing the prediction error is proposed. Numerical experiments are conducted to demonstrate the efficiency of the proposed estimation methods with an application in demand prediction. Hidden Markov Model (HMM) is a bivariate stochastic process such that one of the process is hidden and the other is observable. The distribution of observable sequence depends on the hidden sequence. In a traditional HMM, the hidden states directly affect the observable states but not vice versa. However, in reality, observable sequence may also have effect on the hidden sequence. For this reason, the concept of Interactive Hidden Markov Model (IHMM) is introduced, whose key idea is that the transitions of the hidden states depend on the observable states too. In this thesis, efforts are devoted in building a highorder IHMM where the probability laws governing both observable and hidden states can be written as a pair of high-order stochastic difference equations. We also propose a new model by capturing the effect of observable sequence on the hidden sequence through using the threshold principle. In this case, reference probability methods are adopted in estimating the optimal model parameters, while for unknown threshold parameter, Akaike Information Criterion (AIC) is used. We explore asset allocation problems from both domestic and foreign perspective where asset price dynamics follows autoregressive HMM. The object of an investor is not only to maximize the expected utility of the terminal wealth, but also to ensure that the risk of the portfolio described by the Value-at-Risk (VaR) does not exceed a specified level. In many decision processes, fuzziness is a major source of imprecision. As a perception of usual Markov chains, the definition of fuzzy Markov chains is introduced. Compared to traditional Markov chain models, fuzzy Markov chains are relatively new and many properties of them are still unknown. Due to the potential applications of fuzzy Markov chains, we provide some characterizations to ensure the ergodicity of these chains under both max-min and max-product compositions. / published_or_final_version / Mathematics / Doctoral / Doctor of Philosophy

Simulation and inference of aggregated Markov processes

葉錦元, Yip, Kam-yuen, William. January 1994 (has links)
published_or_final_version / Applied Statistics / Master / Master of Social Sciences

Some results on higher order Markov Chain models

郭慈安, Kwok, Chi-on, Michael. January 1988 (has links)
published_or_final_version / Statistics / Master / Master of Philosophy

Quantum chains

Bose, A. (Amitava) January 1968 (has links)
No description available.

Techniques d'estimation pour les chaînes de Markov y compris les chaînes avec matrice causative constante

Dansereau, Maryse. January 1974 (has links)
No description available.

Large-scale programming in Markov decision processes

Contreras, Luis Eduardo 08 1900 (has links)
No description available.

Curve fitting by Markov transients

Bryant, Douglas John 05 1900 (has links)
No description available.

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