ModelHMMR-class function

A Reference Class which represents a fitted HMMR model.

ModelHMMR represents an estimated HMMR model. class

Fields

• 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.

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 (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 log-likelihood 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.
  

Examples

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

# Log-likelihood:
hmmr$stat$loglik

# Parameters of the polynomial regressions:
hmmr$param$beta

See Also

ParamHMMR , StatHMMR