Some Aspects of Statistical Inference for M-th Order Markov Processes

Some Aspects of Statistical Inference for M-th Order Markov Processes PDF Author: Ramanpillai Krishna Pillai
Publisher:
ISBN:
Category :
Languages : en
Pages : 58

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Some Aspects of Statistical Inference for M-th Order Markov Processes

Some Aspects of Statistical Inference for M-th Order Markov Processes PDF Author: Ramanpillai Krishna Pillai
Publisher:
ISBN:
Category :
Languages : en
Pages : 58

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SOME ASPECTS OF STATISTICAL INFERENCE FOR M-TH ORDER MARKOV PROCESSES..

SOME ASPECTS OF STATISTICAL INFERENCE FOR M-TH ORDER MARKOV PROCESSES.. PDF Author: RAMANPILLAI KRISHNA PILLAI
Publisher:
ISBN:
Category :
Languages : en
Pages : 136

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Statistical Inference for Markov Processes

Statistical Inference for Markov Processes PDF Author: Patrick Billingsley
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 100

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Statistical Inference for Piecewise-deterministic Markov Processes

Statistical Inference for Piecewise-deterministic Markov Processes PDF Author: Romain Azais
Publisher: John Wiley & Sons
ISBN: 1119544033
Category : Mathematics
Languages : en
Pages : 279

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Book Description
Piecewise-deterministic Markov processes form a class of stochastic models with a sizeable scope of applications: biology, insurance, neuroscience, networks, finance... Such processes are defined by a deterministic motion punctuated by random jumps at random times, and offer simple yet challenging models to study. Nevertheless, the issue of statistical estimation of the parameters ruling the jump mechanism is far from trivial. Responding to new developments in the field as well as to current research interests and needs, Statistical inference for piecewise-deterministic Markov processes offers a detailed and comprehensive survey of state-of-the-art results. It covers a wide range of general processes as well as applied models. The present book also dwells on statistics in the context of Markov chains, since piecewise-deterministic Markov processes are characterized by an embedded Markov chain corresponding to the position of the process right after the jumps.

Some Aspects of Statistical Inference in Markov Chains

Some Aspects of Statistical Inference in Markov Chains PDF Author:
Publisher:
ISBN:
Category : Markov processes
Languages : en
Pages : 240

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Inference in Hidden Markov Models

Inference in Hidden Markov Models PDF Author: Olivier Cappé
Publisher: Springer Science & Business Media
ISBN: 0387289828
Category : Mathematics
Languages : en
Pages : 656

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Book Description
This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states. In a unified way the book covers both models with finite state spaces and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Many examples illustrate the algorithms and theory. This book builds on recent developments to present a self-contained view.

Elements of the Theory of Markov Processes and Their Applications

Elements of the Theory of Markov Processes and Their Applications PDF Author: A. T. Bharucha-Reid
Publisher: Courier Corporation
ISBN: 0486150356
Category : Mathematics
Languages : en
Pages : 485

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Book Description
This graduate-level text and reference in probability, with numerous applications to several fields of science, presents nonmeasure-theoretic introduction to theory of Markov processes. The work also covers mathematical models based on the theory, employed in various applied fields. Prerequisites are a knowledge of elementary probability theory, mathematical statistics, and analysis. Appendixes. Bibliographies. 1960 edition.

A Course in Stochastic Processes

A Course in Stochastic Processes PDF Author: Denis Bosq
Publisher: Springer
ISBN: 0792340876
Category : Mathematics
Languages : en
Pages : 354

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Book Description
This text is an Elementary Introduction to Stochastic Processes in discrete and continuous time with an initiation of the statistical inference. The material is standard and classical for a first course in Stochastic Processes at the senior/graduate level (lessons 1-12). To provide students with a view of statistics of stochastic processes, three lessons (13-15) were added. These lessons can be either optional or serve as an introduction to statistical inference with dependent observations. Several points of this text need to be elaborated, (1) The pedagogy is somewhat obvious. Since this text is designed for a one semester course, each lesson can be covered in one week or so. Having in mind a mixed audience of students from different departments (Math ematics, Statistics, Economics, Engineering, etc.) we have presented the material in each lesson in the most simple way, with emphasis on moti vation of concepts, aspects of applications and computational procedures. Basically, we try to explain to beginners questions such as "What is the topic in this lesson?" "Why this topic?", "How to study this topic math ematically?". The exercises at the end of each lesson will deepen the stu dents' understanding of the material, and test their ability to carry out basic computations. Exercises with an asterisk are optional (difficult) and might not be suitable for homework, but should provide food for thought.

Statistical Inference in Markov Chains Using the Principal of Minimum Discrimination Information

Statistical Inference in Markov Chains Using the Principal of Minimum Discrimination Information PDF Author: Said Mohamed Rujbani
Publisher:
ISBN:
Category : Markov processes
Languages : en
Pages : 226

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Statistical Inference for Markov Processes, Reprinted

Statistical Inference for Markov Processes, Reprinted PDF Author: Patrick Billingsley
Publisher:
ISBN:
Category :
Languages : en
Pages :

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