Discrete-valued time series are common in practice, but methods for their analysis are not well-known. In recent years, methods have been developed which are specifically designed for the analysis of discrete-valued time series. Hidden Markov and Other Models for Discrete-Valued Time Series introduc
Hidden Markov and other models for discrete-valued time series
โ Scribed by Iain L. MacDonald, Walter Zucchini
- Publisher
- Chapman & Hall
- Year
- 1997
- Tongue
- English
- Leaves
- 256
- Series
- Monographs on statistics and applied probability 70
- Edition
- 1st ed
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
This book describes a variety of hidden Markov models and points out where they arise and how to estimate parameters of the model. It also points out where they arise in a natural manner and how the models can be used in applications. It is not supposed to be a mathematically rigorous treatment of the subject for which one should look elsewhere like the book by R.J.Elliott, L.Aggoun and J.B.Moore (1995): Hidden Markov Models: Estimation and Control. Springer-Verlag. It is easy to read. But it lacks depth to a certain extent and is not comprehensive enough to satisfy all types of needs.
โฆ Table of Contents
Cover......Page 1
MONOGRAPHS ON STATISTICS AND APPLIED PROBABILITY......Page 3
Title......Page 7
Contents......Page 11
Preface......Page 15
PART ONE Survey of Models......Page 19
1 A survey of Models for discrete-valued time series......Page 21
PART TWO Hidden Markov models......Page 71
2 The basic Models......Page 73
3 Extensions and modifications......Page 127
4 Applications......Page 155
APPENDIX A Proofs of results used in the derivation of the Baurn-Welch algorithm......Page 221
APPENDIX B Data......Page 225
References......Page 235
Author index......Page 245
Subject index......Page 249
๐ SIMILAR VOLUMES
<P><U><EM>Reveals How HMMs Can Be Used as General-Purpose Time Series Models</EM></U></P> <P><EM>Implements all methods in R </EM><STRONG>Hidden Markov Models for Time Series: An Introduction Using R applies hidden Markov models (HMMs) to a wide range of time series types, from continuous-valued, c
Article 20 pp-Vlad Stefan Barbu, Nikolaos Limnios, November 19, 2006<br/>This article presents the reliability of discrete-time semi-Markov systems. After some basic<br/>definitions and notation, we obtain explicit forms for reliability indicators. We propose nonparametric<br/>estimators for reliabi