summary.mhmm | R Documentation |
Function summary.mhmm
gives a summary of a mixture hidden Markov model.
## S3 method for class 'mhmm'
summary(
object,
parameters = FALSE,
conditional_se = TRUE,
log_space = FALSE,
...
)
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 |
log_space |
Make computations using log-space instead of scaling for greater
numerical stability at cost of decreased computational performance. Default is |
... |
Further arguments to |
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.
Transition probabilities. Only returned if parameters = TRUE
.
Emission probabilities. Only returned if parameters = TRUE
.
Initial state probabilities. Only returned if parameters = TRUE
.
Log-likelihood.
Bayesian information criterion.
The most probable cluster according to posterior probabilities.
Coefficients of covariates.
Variance-covariance matrix of coefficients.
Prior cluster probabilities (mixing proportions) given the covariates.
Posterior cluster membership probabilities.
Cluster probabilities (columns) by the most probable cluster (rows).
build_mhmm
and fit_model
for building and
fitting mixture hidden Markov models; and
mhmm_biofam
for information on the model used in examples.
# Loading mixture hidden Markov model (mhmm object)
# of the biofam data
data("mhmm_biofam")
# Model summary
summary(mhmm_biofam)
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