| 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)