SMPracticals (version 1.4-3.1)

MClik: 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)

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

Arguments

d

A sequence containing successive states of the chain

Author

A. C. Davison ([e-mail])

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)