Description Fields Methods See Also Examples
ModelHMMR represents an estimated HMMR model.
param
An object of class ParamHMMR. It contains the estimated values of the parameters.
stat
An object of class StatHMMR. It contains all the statistics associated to the HMMR model.
plot(what = c("predicted", "filtered", "smoothed", "regressors",
"loglikelihood"), ...)
Plot method.
what
The type of graph requested:
"predicted" =
Predicted time series and predicted
regime probabilities (fields predicted
and
predict_prob
of class StatHMMR).
"filtered" =
Filtered time series and filtering
regime probabilities (fields filtered
and
filter_prob
of class StatHMMR).
"smoothed" =
Smoothed time series, and
segmentation (fields smoothed
and klas
of the
class StatHMMR).
"regressors" =
Polynomial regression components
(fields regressors
and tau_tk
of class
StatHMMR).
"loglikelihood" =
Value of the loglikelihood for
each iteration (field stored_loglik
of class
StatHMMR).
...
Other graphics parameters.
By default, all the graphs mentioned above are produced.
summary(digits = getOption("digits"))
Summary method.
digits
The number of significant digits to use when printing.
ParamHMMR, StatHMMR
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15  data(univtoydataset)
hmmr < emHMMR(univtoydataset$x, univtoydataset$y, K = 5, p = 1, verbose = TRUE)
# hmmr is a ModelHMMR object. It contains some methods such as 'summary' and 'plot'
hmmr$summary()
hmmr$plot()
# hmmr has also two fields, stat and param which are reference classes as well
# Loglikelihood:
hmmr$stat$loglik
# Parameters of the polynomial regressions:
hmmr$param$beta

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