hhsmm

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: doi:10.48550/arXiv.2109.12489).