ML: Maximum Likelihood

In BCT: Bayesian Context Trees for Discrete Time Series

Maximum Likelihood

Description

Computes the logarithm of the likelihood of the observations, maximised over all models and parameters.

Usage

ML(input_data, depth)

Arguments

input_data	the sequence to be analysed. The sequence needs to be a "character" object. See the examples section of the BCT/kBCT functions on how to transform any dataset to a "character" object.
depth	maximum memory length.

Value

returns the natural logarithm of the maximum likelihood.

See Also

BCT, kBCT

Examples

# Computing the maximum likelihood of the gene_s dataset 
# with a maximum depth of 5:
ML(gene_s, 5)

BCT documentation built on May 12, 2022, 5:06 p.m.