Mixture Hidden Markov Models for Social Sequence Data and Other Multivariate, Multichannel Categorical Time Series
Bootstrap Sampling of NHMM Coefficients
Build a Hidden Markov Model
Build a Latent Class Model
Build a Mixture Hidden Markov Model
Build a Markov Model
Build a Mixture Markov Model
Set Cluster Names for Mixture Models
Get Cluster Names from Mixture HMMs
Extract the Prior Cluster Probabilities of MHMM or MNHMM
Get the Estimated Regression Coefficients of Non-Homogeneous Hidden Ma...
Transform TraMineR's state sequence object to data.table and vice vers...
Extract the Emission Probabilities of Hidden Markov Model
Estimate a Mixture Non-homogeneous Hidden Markov Model
Estimate a Non-homogeneous Hidden Markov Model
Estimate Parameters of (Mixture) Hidden Markov Models and Their Restri...
Forward and Backward Probabilities for Hidden Markov Model
Compute the Marginal Probabilities from NHMMs
Plot Multidimensional Sequence Plots in a Grid
Most Probable Paths of Hidden States
Extract the Initial State Probabilities of Hidden Markov Model
Log-likelihood of a Hidden Markov Model
Log-likelihood of a Non-homogeneous Hidden Markov Model
Merge Multiple Sequence Objects into One (from Multichannel to Single ...
Transform a Multichannel Hidden Markov Model into a Single Channel Rep...
Extract Most Probable Cluster for Each Sequence
Interactive Stacked Plots of Multichannel Sequences and/or Most Probab...
Number of Observations in Hidden Markov Model
Permute the states of NHMM using Hungarian algorithm
Plot Colorpalettes
Plot hidden Markov models
Interactive Plotting for Mixed Hidden Markov Model (mhmm)
Stack Multichannel Sequence Plots and/or Most Probable Paths Plots fro...
Extract Posterior Cluster Probabilities
Posterior Probabilities for Hidden Markov Models
Predictions from Non-homogeneous Hidden Markov Models
Print Method for a Hidden Markov Model
Objects exported from other packages
Convert return code from estimate_nhmm and estimate_mnhmm to text
Reorganize a mixture hidden Markov model to a list of separate hidden ...
Deprecated function(s) in the seqHMM package
The seqHMM package
Simulate hidden Markov models
Simulate Mixture Hidden Markov Models
Simulate Mixture Non-homogeneous Hidden Markov Models
Simulate Non-homogeneous Hidden Markov Models
Simulate Parameters of Hidden Markov Models
Sort sequences in a sequence object
Define Arguments for Plotting Multichannel Sequences and/or Most Proba...
Stacked Plots of Multichannel Sequences and/or Most Probable Paths fro...
Stacked Sequence Plots of Multichannel Sequences and/or Most Probable ...
Get State Names of Hidden Markov Model
Summary method for mixture hidden Markov models
Summary method for mixture non-homogenous hidden Markov models
Extract the State Transition Probabilities of Hidden Markov Model
Trim Small Probabilities of Hidden Markov Model
Update Covariate Values of NHMM
Variance-Covariance Matrix for Coefficients of Covariates of Mixture H...
Designed for estimating variants of hidden (latent) Markov models (HMMs), mixture HMMs, and non-homogeneous HMMs (NHMMs) for social sequence data and other categorical time series. Special cases include feedback-augmented NHMMs, Markov models without latent layer, mixture Markov models, and latent class models. The package supports models for one or multiple subjects with one or multiple parallel sequences (channels). External covariates can be added to explain cluster membership in mixture models as well as initial, transition and emission probabilities in NHMMs. The package provides functions for evaluating and comparing models, as well as functions for visualizing of multichannel sequence data and HMMs. For NHMMs, methods for computing average causal effects and marginal state and emission probabilities are available. Models are estimated using maximum likelihood via the EM algorithm or direct numerical maximization with analytical gradients. Documentation is available via several vignettes, and Helske and Helske (2019, <doi:10.18637/jss.v088.i03>). For methodology behind the NHMMs, see Helske (2025, <doi:10.48550/arXiv.2503.16014>).