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 **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 **ChrisRedfield** at March 25, 2014

Published: 2014-01-28 | ISBN: 1447163079 | PDF | 300 pages | 3 MB

Posted by **arundhati** at Feb. 13, 2014

2014 | ISBN-10: 1447163079 | 300 pages | PDF | 3,8 MB

Posted by **hill0** at March 5, 2017

English | 18 May 2017 | ISBN: 1493967517 | 232 Pages | PDF | 6.1 MB

This volume aims to provide a new perspective on the broader usage of Hidden Markov Models (HMMs) in biology. Hidden Markov Models: Methods and Protocols guides readers through chapters on biological systems; ranging from single biomolecule,

Posted by **AlenMiler** at Jan. 24, 2017

English | 11 Dec. 2016 | ISBN: 1540809080 | 212 Pages | PDF (True) | 1.58 MB

Master Deep Time Series Forecasting with Python! Deep Time Series Forecasting with Python takes you on a gentle, fun and unhurried practical journey to creating deep neural network models for time series forecasting with Python.

Posted by **step778** at Jan. 16, 2017

2000 | pages: 611 | ISBN: 0521640687 | DJVU | 16,0 mb

Posted by **AlenMiler** at Oct. 29, 2016

English | 23 Oct. 2016 | ISBN: 1539692310 | 207 Pages | PDF | 1.84 MB

In System Identification Toolbox software, MATLAB represents linear systems as model objects. Model objects are specialized data containers that encapsulate model data and other attributes in a structured way.