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seqHMM

Mixture Hidden Markov Models for Social Sequence Data and Other Multivariate, Multichannel Categorical Time Series

Designed for fitting hidden (latent) Markov models and mixture hidden Markov models for social sequence data and other categorical time series. Also some more restricted versions of these type of models are available: Markov models, 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. The package provides functions for evaluating and comparing models, as well as functions for visualizing of multichannel sequence data and hidden Markov models. Models are estimated using maximum likelihood via the EM algorithm and/or direct numerical maximization with analytical gradients. All main algorithms are written in C++ with support for parallel computation. Documentation is available via several vignettes in this page, and the paper by Helske and Helske (2019, <doi:10.18637/jss.v088.i03>).

Functions (39)

TraMineR_imports

Imported Functions from TraMineR

biofam3c

Three-channel biofam data

build_hmm

Build a Hidden Markov Model

build_lcm

Build a Latent Class Model

build_mhmm

Build a Mixture Hidden Markov Model

build_mm

Build a Markov Model

build_mmm

Build a Mixture Markov Model

colorpalette

Color palettes

estimate_coef

Estimate Regression Coefficients of Mixture Hidden Markov Models

fit_model

Estimate Parameters of (Mixture) Hidden Markov Models and Their Restricted Variants

forward_backward

Forward and Backward Probabilities for Hidden Markov Model

gridplot

Plot Multidimensional Sequence Plots in a Grid

hidden_paths

Most Probable Paths of Hidden States

hmm_biofam

Hidden Markov model for the biofam data

hmm_mvad

Hidden Markov model for the mvad data

logLik.hmm

Log-likelihood of the Hidden Markov Model

logLik.mhmm

Log-likelihood of the Mixture Hidden Markov Model

mc_to_sc

Transform a Multichannel Hidden Markov Model into a Single Channel Representation

mc_to_sc_data

Merge Multiple Sequence Objects into One (from Multichannel to Single Channel Data)

mhmm_biofam

Mixture hidden Markov model for the biofam data

mhmm_mvad

Mixture hidden Markov model for the mvad data

mssplot

Interactive Stacked Plots of Multichannel Sequences and/or Most Probable Paths for Mixture Hidden Markov Models

plot.hmm

Plot hidden Markov models

plot.mhmm

Interactive Plotting for Mixed Hidden Markov Model (mhmm)

plot.ssp

Stack Multichannel Sequence Plots and/or Most Probable Paths Plots from Hidden Markov Models

plot_colors

Plot Colorpalettes

posterior_probs

Posterior Probabilities for (Mixture) Hidden Markov Models

print

Print Method for a Hidden Markov Model

separate_mhmm

Reorganize a mixture hidden Markov model to a list of separate hidden Markov models (covariates ignored)

seqHMM

The seqHMM package

seqHMM-deprecated

Deprecated function(s) in the seqHMM package

simulate_hmm

Simulate hidden Markov models

simulate_mhmm

Simulate Mixture Hidden Markov Models

simulate_pars

Simulate Parameters of Hidden Markov Models

ssp

Define Arguments for Plotting Multichannel Sequences and/or Most Probable Paths from Hidden Markov Models

ssplot

Stacked Plots of Multichannel Sequences and/or Most Probable Paths from Hidden Markov Models

summary.mhmm

Summary method for mixture hidden Markov models

trim_model

Trim Small Probabilities of Hidden Markov Model

vcov.mhmm

Variance-Covariance Matrix for Coefficients of Covariates of Mixture Hidden Markov Model

seqHMM

Mixture Hidden Markov Models for Social Sequence Data and Other Multivariate, Multichannel Categorical Time Series

v1.0.14

GPL (>= 2)

Authors

Jouni Helske [aut, cre] (<https://orcid.org/0000-0001-7130-793X>), Satu Helske [aut] (<https://orcid.org/0000-0003-0532-0153>)

Initial release

2019-10-21

seqHMM

Functions (39)

seqHMM

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