Man pages for luisdamiano/BayesHMM
Full Bayesian Inference for Hidden Markov Models

browse_modelLoad the underlying Stan code into an IDE or browser...
checkVerify that the object is a valid specification. TO BE...
classify_alphaClassify observations based on filtered probabilities.
classify_gammaClassify observations based on smoothed probabilities.
classify_quantityClassify observations based on latent state probabilities.
classify_zstarAssign the hidden states to the most likely path (_zstar_).
compileCompile a specified model.
DensityCreate a representation of a probability mass or density...
explainCreate an user-friendly text describing the model.
explain_initialCreate an outline of the initial distribution model.
explain_observationCreate an outline of the observation model.
explain_transitionCreate an outline of the transition model.
extractExtract quantities from a model fitted with BayesHMM.
extract_alphaExtract the estimates of the filtered probability (alpha).
extract_bestReturn the optimization object for the run with the hightest...
extract_dataExtract the dataset used to fit the model.
extract_filenameExtract the path to file with the underlying Stan code...
extract_gammaExtract the estimates of the smoothed probability (gamma).
extract_gridExtract summary results from the optimization procedure.
extract_grid.OptimizationExtract summary results from the optimization procedure.
extract_grid.OptimizationListExtract summary results from more than one run of the...
extract_KExtract the number of hidden states _K_.
extract_n_chainsExtract the number of chains (M).
extract_obs_parametersExtract the estimates of the observation model parameters.
extract_parameter_namesExtract the names of all the model parameters in the fit...
extract_parametersExtract the estimates of the model parameters (observation,...
extract_quantityExtract estimated quantities from fit objects.
extract_RExtract the dimension of the observation vector _R_.
extract_seedExtract the time elapsed when fitting the model.
extract_specExtract the specification object used to fit the model...
extract_TExtract the length of the time series _T_.
extract_timeExtract the time elapsed when fitting the model.
extract_yExtract the obsevation matrix used to fit the model _y_.
extract_ypredExtract the sample of the observation variable drawn from the...
extract_ysimExtract the simulated sample of the observation variable...
extract_zpredExtract the sample of the hidden state path drawn from the...
extract_zstarExtract the estimates of the most likely hidden state...
fitFit a model by MCMC
get_current_themeReturn the current theme.
get_default_themeReturn the default theme.
get_plot_themeReturn the current theme for visualizations.
get_print_settingsReturn the current theme for text printouts.
hmmSpecify a Hidden Markov Model
is.stanfitCheck if it is an object created by 'sampling'.
is.stanoptimVerify that the object was created by 'optimizing'.
load_themeLoads a theme into the R session.
make_text_headerMake a string with a header.
make_text_lineMake a string with a line (horizontal rule).
make_text_subheaderMake a string with a subheader.
mixtureSpecify a mixture model
optimizingFit a model by MAP
optimizing_allRun several instances of the optimization algorithm.
optimizing_bestRun several instances of the optimization algorithm.
optimizing_runRun one instance of the
plot_ppredictivePlot samples drawn from the posterior predictive density.
plot_seriesPlot the observation series along with many other...
plot_state_probabilityPlot the estimated hidden path along with many other...
runRun a Markov-chain Monte Carlo algorithm to sample from the...
samplingDraw samples from a specification.
select_all_parametersReturn the name of all model parameters.
select_initial_parametersReturn the name of the initial model parameters.
select_obs_parametersReturn the name of the observation model parameters.
select_parametersReturn the name of the model parameters.
select_transition_parametersReturn the name of the transition model parameters.
simSimulate data from the prior predictive density.
specifySpecify a model.
themeTheme for BayesHMM visualizations and printouts
validate_calibrationValidate a model via a procedure based on simulated data.
luisdamiano/BayesHMM documentation built on Nov. 8, 2018, 8:48 p.m.