summary.mhmm {seqHMM} | R Documentation |
Summary method for mixture hidden Markov models
Description
Function summary.mhmm
gives a summary of a mixture hidden Markov model.
Usage
## S3 method for class 'mhmm'
summary(object, parameters = FALSE, conditional_se = TRUE, ...)
Arguments
object |
Mixture hidden Markov model of class |
parameters |
Whether or not to return transition, emission, and
initial probabilities. |
conditional_se |
Return conditional standard errors of coefficients.
See |
... |
Further arguments to |
Details
The summary.mhmm
function computes features from a mixture hidden Markov
model and stores them as a list. A print
method prints summaries of these:
log-likelihood and BIC, coefficients and standard errors of covariates, means of prior
cluster probabilities, and information on most probable clusters.
Value
transition_probs
Transition probabilities. Only returned ifparameters = TRUE
.emission_probs
Emission probabilities. Only returned ifparameters = TRUE
.initial_probs
Initial state probabilities. Only returned ifparameters = TRUE
.logLik
Log-likelihood.BIC
Bayesian information criterion.most_probable_cluster
The most probable cluster according to posterior probabilities.coefficients
Coefficients of covariates.vcov
Variance-covariance matrix of coefficients.prior_cluster_probabilities
Prior cluster probabilities (mixing proportions) given the covariates.posterior_cluster_probabilities
Posterior cluster membership probabilities.classification_table
Cluster probabilities (columns) by the most probable cluster (rows).
See Also
build_mhmm()
and fit_model()
for building and
fitting mixture hidden Markov models; and
mhmm_biofam()
for information on the model used in examples.
Examples
# Loading mixture hidden Markov model (mhmm object)
# of the biofam data
data("mhmm_biofam")
# Model summary
summary(mhmm_biofam)