c(person("Morteza", "Amini", role = c("aut", "cre","cph"),
email = "morteza.amini@ut.ac.ir"),
person("Afarin", "Bayat", role = "aut"),
person("Reza", "Salehian", role = "aut"))
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, and many other useful tools
(read for more description: <arXiv:2109.12489>).
Morteza Amini [aut, cre, cph],
Afarin Bayat [aut],
Reza Salehian [aut]

Rcpp, Rdpack, MASS, mice, cpr, psych, progress

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: <arXiv:2109.12489>).
Rcpp, Rdpack, MASS, mice, cpr, psych, progress, magic,
splines2

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>).