Hidden Markov Models for Time Series: An Introduction Using R (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)
The book would be a good text for a seminar or a course on HMM or for self-learning the topic. … Those who have the background necessary to use the R code and to replicate the results throughout the book will find plenty of material in this book to extend what they learn to their own data. The book is written very pedagogically … all the data sets, errata sheet, R code, among other things, can be accessed at the web site.—Journal of Statistical Software, Vol. 43, October 2011… this book has a very nice mix of probability, statistics, and data analysis. It is suitable for a course in stochastic modeling using hidden Markov models, but also serves well as an introduction for nonspecialists.—Biometrics, 67, September 2011… this is an excellent book, which should be of great interest to applied statisticians looking for a clear introduction to HMMs and advice on the practical implementation of these models. It is also an ideal teaching resource.—Australian & New Zealand Journal of Statistics, 2011It is clear that much care has gone into this book: it has a very detailed contents list, a list of abbreviations and notations, thoughtful data analyses, many references and a detailed index. In fact, it would be difficult not to thoroughly recommend it to anyone interested in learning how to tackle these types of data.—International Statistical Review(2011), 79, 1