bookApr 28, 2009Closed access

Hidden Markov Models for Time Series: An Introduction Using R

University of Göttingen

Abstract

Illustrates the flexibility of HMMs as general-purpose models for time series data. This work presents an 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.

Citation impact

716
total citations
FWCI
7.30
Percentile
100%
References
88
Citations per year

Authors

2

Topics & keywords

Keywords
  • Hidden Markov model
  • Markov chain
  • Hidden semi-Markov model
  • Mathematics
  • Model selection
  • Expectation–maximization algorithm
  • Gibbs sampling
  • Markov model
No related works found for this paper.