summary.mhmm: Summarizing multivariate Hidden Markov Models

In hmmhdd: Hidden Markov Models for High Dimensional Data

Description

summary method for class "mhmm".

Usage

## S3 method for class 'mhmm'
summary(object, ...)

Arguments

object	an object of class "mhmm", a result of a call to fitBM_mhmm
...	additional arguments affecting the summary produced.

Value

The function "summary.mhmm" returns a list of summary statistics for a hidden markov model obtained through the Baum-Welch algorithm.

References

Martino A., Guatteri, G. and Paganoni A. M., Multivariate Hidden Markov Models for disease progression, Mox Report 59/2018, 2018

See Also

fitBM_mhmm

Examples

data(copulahmmdata)
Obs <- copulahmmdata
n <- 20 #number of statistical units
n_tot <- 5000 #total number of observations
bt <- seq(1, n_tot, by = n)
distr <- c("exp", "gaussian")
#Initialize the HMM
parameters <- list(as.matrix(c(1,0.25)), matrix(c(3, -1, 1, 1), nrow = 2))
corr <- array(c(1, 0.4, 0.4, 1, 1, 0.1, 0.1, 1), dim = c(2, 2, 2))
hmm <- set_mhmm(Obs, bT = bt, nStates = 2, params = parameters, corr = corr, distr = distr)
# Compute the parameters of the HMM with the Baum-Welch algorithm
bw <- fitBM_mhmm(hmm)

summary(bw)

hmmhdd documentation built on Sept. 4, 2019, 5:03 p.m.