viterbi: Computes the most probable path of states
In HMM: Hidden Markov Models

View source: R/HMM.r

viterbi

R Documentation

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.

Format

Dimension and Format of the Arguments.

hmm: A valid Hidden Markov Model, for example instantiated by initHMM.
observation: A vector of observations.

Value

Return Value:

viterbiPath

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

Author(s)

Lin Himmelmann <hmm@linhi.com>, Scientific Software Development

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

# 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)

HMM documentation built on March 23, 2022, 5:06 p.m.