mchain: Markov Chain Object

In HiddenMarkov: Hidden Markov Models

Markov Chain Object

Description

Creates a Markov chain object with class "mchain". It does not simulate data.

Usage

mchain(x, Pi, delta, nonstat = TRUE)

Arguments

x	is a vector of length n containing the observed process, else it is specified as NULL. This is used when there are no data and a process is to be simulated.
Pi	is the m \times m transition probability matrix of the Markov chain.
delta	is the marginal probability distribution of the m state Markov chain at the first time point.
nonstat	is logical, TRUE if the homogeneous Markov chain is assumed to be non-stationary, default. See “Details” below.

Value

A list object with class "mchain", containing the above arguments as named components.

Examples

Pi <- matrix(c(0.8, 0.2,
               0.3, 0.7),
             byrow=TRUE, nrow=2)

#    Create a Markov chain object with no data (NULL)
x <- mchain(NULL, Pi, c(0,1))

#    Simulate some data
x <- simulate(x, nsim=2000)

#   estimate transition probabilities
estPi <- table(x$mc[-length(x$mc)], x$mc[-1])
rowtotal <- estPi %*% matrix(1, nrow=nrow(Pi), ncol=1)
estPi <- diag(as.vector(1/rowtotal)) %*% estPi
print(estPi)

HiddenMarkov documentation built on April 3, 2025, 6:22 p.m.