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 1.4-3.1 Index]