ModelMixHMMR-class: A Reference Class which represents a fitted mixture of HMMR...

In fchamroukhi/mixHMMR: Mixture of Hidden Markov Model Regression ('mixHMMR') for Simultaneous Curve Clustering and Segmentation

Description

ModelMixHMMR represents an estimated mixture of HMMR model.

Fields

param

A ParamMixHMMR object. It contains the estimated values of the parameters.

stat

A StatMixHMMR object. It contains all the statistics associated to the MixHMMR model.

Methods

plot(what = c("clustered", "smoothed", "loglikelihood"), ...)

Plot method

what

The type of graph requested:

• "clustered" = Clustered curves (field klas of class StatMixHMMR).

• "smoothed" = Smoothed signal (field smoothed of class StatMixHMMR).

• "loglikelihood" = Value of the log-likelihood for each iteration (field stored_loglik of class StatMixHMMR).

...

Other graphics parameters.

summary(digits = getOption("digits"))

Summary method.

digits

The number of significant digits to use when printing.

See Also

ParamMixHMMR, StatMixHMMR

Examples

data(toydataset)
x <- toydataset$x
Y <- t(toydataset[,2:ncol(toydataset)])

mixhmmr <- emMixHMMR(X = x, Y = Y, K = 3, R = 3, p = 1, verbose = TRUE)

# mixhmmr is a ModelMixHMMR object. It contains some methods such as 'summary' and 'plot'
mixhmmr$summary()
mixhmmr$plot()

# mixhmmr has also two fields, stat and param which are reference classes as well

# Log-likelihood:
mixhmmr$stat$loglik

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

fchamroukhi/mixHMMR documentation built on Aug. 8, 2019, 3:31 p.m.