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Authors: Ingmar Visser, Maarten Speekenbrink
Title: [download]
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depmixS4: An R Package for Hidden Markov Models
Reference: Vol. 36, Issue 7, Aug 2010
Submitted 2009-08-19, Accepted 2010-06-21
Type: Article
Abstract:

depmixS4 implements a general framework for defining and estimating dependent mixture models in the R programming language. This includes standard Markov models, latent/hidden Markov models, and latent class and finite mixture distribution models. The models can be fitted on mixed multivariate data with distributions from the glm family, the (logistic) multinomial, or the multivariate normal distribution. Other distributions can be added easily, and an example is provided with the exgaus distribution. Parameters are estimated by the expectation-maximization (EM) algorithm or, when (linear) constraints are imposed on the parameters, by direct numerical optimization with the Rsolnp or Rdonlp2 routines.

Paper: [download]
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depmixS4: An R Package for Hidden Markov Models
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Supplements: [download]
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depmixS4_1.0-0.tar.gz: R source package
(application/x-gzip, 541 KB)
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v36i07.R: R example code from the paper
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Resources: BibTeX | OAI
Creative Commons License
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.
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