Scientific Software Development - Dr. Lin Himmelmann,
www.linhi.com
Easy to use library to setup, apply and make inference
with discrete time and discrete space Hidden Markov Models

Hidden Markov Model for Continuous Observations Processes
The package includes the functions designed to analyse continuous observations processes with the Hidden Markov Model approach. They include Baum-Welch and Viterbi algorithms and additional visualisation functions. The observations are assumed to have Gaussian distribution and to be weakly stationary processes. The package was created for analyses of financial time series, but can also be applied to any continuous observations processes.

A Fast Solver for Henderson Mixed Model Equation via Row
Operations
Consider the linear mixed model with normal random effects. A typical method to solve Henderson's Mixed Model Equations (HMME) is recursive estimation of the fixed effects and random effects. We provide a fast, stable, and scalable solver to the HMME without computing matrix inverse. See Kim (2017) <arXiv:1710.09663> for more details.
Jiwoong Kim [aut],
Kisung You [aut, cre]

Markov Regime Switching Copula Models Estimation and Goodness of
Fit
Mamadou Yamar Thioub <mamadou-yamar.thioub@hec.ca>,
Bouchra Nasri <bouchra.nasri@mail.mcgill.ca>,
Romanic Pieugueu <romanic.pieugueu@gerad.ca>, and
Bruno Remillard <bruno.remillard@hec.ca>
R functions to estimate and perform goodness of fit test for several
Markov regime switching and mixture bivariate copula models.
The goodness of fit test is based on a Cramer von Mises statistic and
uses the Rosenblatt transform and parametric bootstrap to estimate the p-value.
The estimation of the copula parameters are based on the pseudo-maximum likelihood
method using pseudo-observations defined as normalized ranks.
matrixcalc, mvtnorm, foreach, doParallel, copula

Mamadou Yamar Thioub <mamadou-yamar.thioub@hec.ca>,
Bouchra Nasri <bouchra.nasri@umontreal.ca>,
Romanic Pieugueu <romanic.pieugueu@gerad.ca>, and
Bruno Remillard <bruno.remillard@hec.ca>