hhsmm: Hidden Hybrid Markov/Semi-Markov Model Fitting

Develops algorithms for fitting, prediction, simulation and initialization of the hidden hybrid Markov/semi-Markov model, introduced by Guedon (2005) <doi:10.1016/j.csda.2004.05.033>, which also includes several tools for handling missing data, nonparametric mixture of B-splines emissions (Langrock et al., 2015 <doi:10.1111/biom.12282>), fitting regime switching regression (Kim et al., 2008 <doi:10.1016/j.jeconom.2007.10.002>) and auto-regressive hidden hybrid Markov/semi-Markov model, spline-based nonparametric estimation of additive state-switching models (Langrock et al., 2018 <doi:10.1111/stan.12133>) and many other useful tools (read for more description: Amini et al., 2022 <doi:10.1007/s00180-022-01248-x> and its arxiv version: <arXiv:2109.12489>).

Getting started

Package details

AuthorMorteza Amini [aut, cre, cph], Afarin Bayat [aut], Reza Salehian [aut]
MaintainerMorteza Amini <morteza.amini@ut.ac.ir>
Package repositoryView on CRAN
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hhsmm documentation built on Aug. 5, 2022, 5:10 p.m.