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Hidden Markov Models for Time Series: An Introduction Using R (Monographs on Statistics and Applied Probability)
Hidden Markov Models for Time Series: An Introduction Using R (Monographs on Statistics and Applied Probability) Summary:By Walter Zucchini, Iain L. MacDonald
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. Please select one mirror to download
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NEWER EBOOKSOLDER EBOOKSSponsored LinksHidden Markov Models for Time Series: An Introduction Using R (Monographs on Statistics and Applied Probability) Keywordsseries data models hmms sociology authors employ freely climatology behavior explores observations variety applications finance epidemiology environment forecasting decoding sets analyzed online checking selection general purpose models accessible overview wonderful flexibility applied probability markov models hidden markovBookmark Hidden Markov Models for Time Series: An Introduction Using R (Monographs on Statistics and Applied Probability)Hyperlink code:
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