ModelMHMMR-class {samurais} | R Documentation |
A Reference Class which represents a fitted MHMMR model.
Description
ModelMHMMR represents an estimated MHMMR model.
Fields
param
A ParamMHMMR object. It contains the estimated values of the parameters.
stat
A StatMHMMR object. It contains all the statistics associated to the MHMMR model.
Methods
plot(what = c("predicted", "filtered", "smoothed", "regressors", "loglikelihood"), ...)
Plot method.
what
The type of graph requested:
-
"predicted" =
Predicted time series and predicted regime probabilities (fieldspredicted
andpredict_prob
of class StatMHMMR). -
"filtered" =
Filtered time series and filtering regime probabilities (fieldsfiltered
andfilter_prob
of class StatMHMMR). -
"smoothed" =
Smoothed time series, and segmentation (fieldssmoothed
andklas
of class StatMHMMR). -
"regressors" =
Polynomial regression components (fieldsregressors
andtau_tk
of class StatMHMMR). -
"loglikelihood" =
Value of the log-likelihood for each iteration (fieldstored_loglik
of class StatMHMMR).
-
...
Other graphics parameters.
By default, all the above graphs are produced.
summary(digits = getOption("digits"))
Summary method.
digits
The number of significant digits to use when printing.
See Also
Examples
data(multivtoydataset)
mhmmr <- emMHMMR(multivtoydataset$x, multivtoydataset[,c("y1", "y2", "y3")],
K = 5, p = 1, verbose = TRUE)
# mhmmr is a ModelMHMMR object. It contains some methods such as 'summary' and 'plot'
mhmmr$summary()
mhmmr$plot()
# mhmmr has also two fields, stat and param which are reference classes as well
# Log-likelihood:
mhmmr$stat$loglik
# Parameters of the polynomial regressions:
mhmmr$param$beta