Man pages for bayesdfa
Bayesian Dynamic Factor Analysis (DFA) with 'Stan'

bayesdfa-packageThe 'bayesdfa' package.
dfa_cvApply cross validation to DFA model
dfa_fittedGet the fitted values from a DFA as a data frame
dfa_loadingsGet the loadings from a DFA as a data frame
dfa_trendsGet the trends from a DFA as a data frame
find_dfa_trendsFind the best number of trends according to LOOIC
find_inverted_chainsFind which chains to invert
find_regimesFit multiple models with differing numbers of regimes to...
find_swansFind outlying "black swan" jumps in trends
fit_dfaFit a Bayesian DFA
fit_regimesFit models with differing numbers of regimes to trend data
hmm_initCreate initial values for the HMM model.
invert_chainsInvert chains
is_convergedSummarize Rhat convergence statistics across parameters
looLOO information criteria
plot_fittedPlot the fitted values from a DFA
plot_loadingsPlot the loadings from a DFA
plot_regime_modelPlot the state probabilities from 'find_regimes()'
plot_trendsPlot the trends from a DFA
predictedCalculate predicted value from DFA object
rotate_trendsRotate the trends from a DFA
sim_dfaSimulate from a DFA
trend_corEstimate the correlation between a DFA trend and some other...
bayesdfa documentation built on May 29, 2021, 1:06 a.m.