MClik {SMPracticals}R Documentation

Likelihood Estimation for Markov Chains

Description

Computes maximum likelihood estimates of transition probabilities for stationary Markov chain models, of order 0 (independence) to 3.

This is intended for use with Practical 6.1 of Davison (2003), not as production code.

Usage

MClik(d)

Arguments

d A sequence containing successive states of the chain

Value

order order of fitted chain
df degrees of freedom using in fitting
L maximum log likelihood for each order
AIC Akaike information criterion for each order
one one-way marginal table of counts
two two-way margin table of transitions
three three-way marginal table of transitions
four four-way marginal table of transitions

Author(s)

A. C. Davison (Anthony.Davison@epfl.ch)

References

Avery, P. J. and Henderson, D. A. (1999) Fitting Markov chain models to discrete state series such as DNA sequences. Applied Statistics, 48, 53–61.

Davison, A. C. (2003) Statistical Models. Cambridge University Press. Section 6.1.

Examples

data(intron)

fit <- MClik(intron)

[Package SMPracticals version 1.3 Index]