Statistical Inference for Partially Observed Markov Processes via the R Package pomp

Statistical Inference for Partially Observed Markov Processes via the R Package pomp

Partially observed Markov process (POMP) models, also known as hidden Markov models or state space models, are ubiquitous tools for time series analysis. The R package pomp provides a very flexible framework for Monte Carlo statistical investigations using nonlinear, non-Gaussian POMP models. A rang...

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Bibliographic Details
Main Authors: Aaron A. King, Dao Nguyen, Edward L. Ionides
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2016-03-01
Series:Journal of Statistical Software
Subjects:
Markov processes
hidden Markov model
state space model
stochastic dynamical system
maximum likelihood
plug-and-play
time series
mechanistic model
sequential Monte Carlo
R
Online Access:https://www.jstatsoft.org/index.php/jss/article/view/2614

Internet

https://www.jstatsoft.org/index.php/jss/article/view/2614

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