Hidden Markov Models For Time Series

Hidden Markov Models for Time Series: An Introduction Using R, Second Edition  eBooks & eLearning

Posted by arundhati at Dec. 9, 2016
Hidden Markov Models for Time Series: An Introduction Using R, Second Edition

Walter Zucchini, Iain L. MacDonald, "Hidden Markov Models for Time Series: An Introduction Using R, Second Edition"
2016 | ISBN-10: 1482253836 | 398 pages | PDF | 46 MB

Hidden Markov Models for Time Series: An Introduction Using R [Repost]  eBooks & eLearning

Posted by ChrisRedfield at April 25, 2015
Hidden Markov Models for Time Series: An Introduction Using R [Repost]

Walter Zucchini, Iain L. MacDonald - Hidden Markov Models for Time Series: An Introduction Using R
Published: 2009-04-28 | ISBN: 1584885734 | PDF | 269 pages | 2 MB
Hidden Markov Models for Time Series: An Introduction Using R (Monographs on Statistics and Applied Probability)

Hidden Markov Models for Time Series
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.

Hidden Markov Models for Bioinformatics (Computational Biology) by T. Koski [Repost]

Hidden Markov Models for Bioinformatics (Computational Biology) by T. Koski
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…
Markov Models for Pattern Recognition: From Theory to Applications, 2nd edition (repost)

Gernot A. Fink, "Markov Models for Pattern Recognition: From Theory to Applications, 2nd edition"
2014 | ISBN-10: 1447163079 | 300 pages | PDF | 3,8 MB
Neural Networks for Time Series Forecasting with R: An Intuitive Step by Step Blueprint for Beginners

Neural Networks for Time Series Forecasting with R: An Intuitive Step by Step Blueprint for Beginners by N.D Lewis
English | 9 Apr. 2017 | ASIN: B06Y5F38P3 | 238 Pages | PDF | 2.01 MB

Markov Models for Pattern Recognition: From Theory to Applications (2nd edition) [Repost]  eBooks & eLearning

Posted by ChrisRedfield at March 25, 2014
Markov Models for Pattern Recognition: From Theory to Applications (2nd edition) [Repost]

Gernot A. Fink - Markov Models for Pattern Recognition: From Theory to Applications (2nd edition)
Published: 2014-01-28 | ISBN: 1447163079 | PDF | 300 pages | 3 MB

Markov Models for Pattern Recognition: From Theory to Applications, 2nd edition  eBooks & eLearning

Posted by arundhati at Feb. 13, 2014
Markov Models for Pattern Recognition: From Theory to Applications, 2nd edition

Gernot A. Fink, "Markov Models for Pattern Recognition: From Theory to Applications, 2nd edition"
2014 | ISBN-10: 1447163079 | 300 pages | PDF | 3,8 MB
Ensembles of Type 2 Fuzzy Neural Models and Their Optimization with Bio-Inspired Algorithms for Time Series Prediction

Ensembles of Type 2 Fuzzy Neural Models and Their Optimization with Bio-Inspired Algorithms for Time Series Prediction By Jesus Soto
English | PDF,EPUB | 2017 (2018 Edition) | 103 Pages | ISBN : 3319712632 | 9.15 MB

This book focuses on the fields of hybrid intelligent systems based on fuzzy systems, neural networks, bio-inspired algorithms and time series. This book describes the construction of ensembles of Interval Type-2 Fuzzy Neural Networks models and the optimization of their fuzzy integrators with bio-inspired algorithms for time series prediction. Interval type-2 and type-1 fuzzy systems are used to integrate the outputs of the Ensemble of Interval Type-2 Fuzzy Neural Network models. Genetic Algorithms and Particle Swarm Optimization are the Bio-Inspired algorithms used for the optimization of the fuzzy response integrators.
Hidden Markov Models in Finance: Further Developments and Applications, Volume II (repost)

Hidden Markov Models in Finance: Further Developments and Applications, Volume II by Rogemar S. Mamon and Robert J. Elliott
English | 2014 | ISBN: 1489974415 | 261 pages | PDF | 4,6 MB