SMPracticals (version 1.3-1)

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)

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

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)