Bayesian NHMM modeling (multiple time series)
Bayesian NHMM modeling for multiple time series. The emission distribution can be mixtures of Gammas, Poissons, Normals and zero inflation is possible.

Bayesian NHMM Modeling (Multiple Time Series)

Bayesian Non-Homogenous Markov and Mixture Models (Multiple Time
Series)
Bayesian HMM and NHMM modeling for multiple time series. The emission distribution can be mixtures of Gammas, Poissons, Normals and zero inflation is possible.

Bayesian HMM and NHMM modeling for multiple time series. The
emission distribution can be mixtures of Gammas, Poissons, Normals and zero
inflation is possible.

The NHMMfdr package implements the non-homogeneous Hidden Markov Model based FDR control as described in Kuan et al., 2011 for multiple comparison adjustment under dependence. It allows for prior information to be incorporated in the model to improve detection of significant tests.

Non-Homogeneous Markov Switching Autoregressive Models: Fitting,
Simulating, Validating.
Calibration, simulation, validation of (non-)homogeneous Markov switching autoregressive models with Gaussian or von Mises innovations.

Non-Homogeneous Markov Switching Autoregressive Models
Calibration, simulation, validation of (non-)homogeneous Markov switching autoregressive models with Gaussian or von Mises innovations.  Penalization methods are implemented for Markov Switching Vector Autoregressive Models of order 1 only.

Calibration, simulation, validation of (non-)homogeneous Markov switching autoregressive models with Gaussian or von Mises innovations.  Penalization methods are implemented for Markov Switching Vector Autoregressive Models of order 1 only. Most functions of the package handle missing values.

ucminf, lars, SIS, caTools, glasso, ncvreg

Modelling and validation of non homogeneous Poisson processes
Tools for modelling, ML estimation, validation analysis
and simulation of non homogeneous Poisson processes in time.

Tools for modelling, ML estimation, validation analysis and simulation of non homogeneous Poisson processes in time.