HMM (version 1.0.1)

viterbi: Computes the most probable path of states

Description

The Viterbi-algorithm computes the most probable path of states for a sequence of observations for a given Hidden Markov Model.

Usage

viterbi(hmm, observation)

Arguments

hmm

A Hidden Markov Model.

observation

A sequence of observations.

Value

Return Value:

viterbiPath

A vector of strings, containing the most probable path of states.

Format

Dimension and Format of the Arguments.

hmm

A valid Hidden Markov Model, for example instantiated by initHMM.

observation

A vector of observations.

References

Lawrence R. Rabiner: A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition. Proceedings of the IEEE 77(2) p.257-286, 1989.

Examples

# NOT RUN {
# Initialise HMM
hmm = initHMM(c("A","B"), c("L","R"), transProbs=matrix(c(.6,.4,.4,.6),2),
	emissionProbs=matrix(c(.6,.4,.4,.6),2))
print(hmm)
# Sequence of observations
observations = c("L","L","R","R")
# Calculate Viterbi path
viterbi = viterbi(hmm,observations)
print(viterbi)
# }