Posted by **arundhati** at Dec. 9, 2016

2016 | ISBN-10: 1482253836 | 398 pages | PDF | 46 MB

Posted by **ChrisRedfield** at April 25, 2015

Published: 2009-04-28 | ISBN: 1584885734 | PDF | 269 pages | 2 MB

Posted by **puliraja** at June 18, 2009

Walter Zucchini, Iain L. MacDonald | Chapman & Hall/CRC | 2009-04-28 | ISBN:1584885734 | Pages: 269 | PDF | 5.3MB

This book illustrates the wonderful flexibility of HMMs as general-purpose models for time series data. It presents an accessible overview of HMMs for analyzing time series data, from continuous-valued, circular, and multivariate series to binary data, bounded and unbounded counts, and categorical observations. It explores a variety of applications in animal behavior, finance, epidemiology, climatology, and sociology. The authors discuss how to employ the freely available computing environment R to carry out computations for parameter estimation, model selection and checking, decoding, and forecasting. They provide all of the data sets analyzed in the text online.

Posted by **enmoys** at June 11, 2016

2005 | 342 Pages | ISBN: 0470022981 , 0470022973 | PDF | 3 MB

Posted by **BUGSY** at May 27, 2015

English | Nov 30, 2001 | ISBN: 1402001363 | 404 Pages | DJVU | 2 MB

The purpose of this book is to give a thorough and systematic introduction to probabilistic modeling in bioinformatics. The book contains a mathematically strict and extensive presentation of the kind of probabilistic models…

Posted by **nebulae** at May 14, 2014

English | 2000 | ISBN: 0471889482 | 288 pages | PDF | 3,2 MB

Posted by **enmoys** at April 13, 2014

2005 | 342 Pages | ISBN: 0470022981 , 0470022973 | PDF | 3 MB

Posted by **nebulae** at Dec. 3, 2013

English | 2010 | ISBN: 3642126006 | 420 pages | PDF | 14 MB

Posted by **arundhati** at Aug. 4, 2013

2000 | ISBN: 0471889482 | 288 pages | PDF | 3,2 MB

Posted by **lenami** at Oct. 24, 2010

Publisher: Chapman & Hall | ISBN: 0412716402 | edition 1996 | PDF | 304 pages | 12 mb

"As an introduction to techniques for analyzing discrete time series, this textbook explains probability models, the spectral density function, time-invariant linear systems, state-space models, nonlinear models, and multivariate time series models."-"Book News, Inc."

This tidy book is a highly readable, introductory survey to the topic of modern time series analysis. It excels in its ability to focus on the more intuitive aspects of analysis and model identification. The discussion of both time- and frequency-domain approaches is reasonably balanced, and Kalman filtering is also introduced.