runHomHMM {snapCGH}R Documentation

A function to fit unsupervised Hidden Markov model

Description

This function fits an unsupervised Hidden Markov model to a given MAList or \code{SegList}

Usage

runHomHMM(input, vr = 0.01,
                maxiter = 100, criteria = "AIC", delta = NA,
                full.output = FALSE, eps = 0.01)

Arguments

input an object of class MAList or SegList
vr Gets passed to the function hidden as the pshape arguement.
maxiter Gets passed to the function hidden as the iterlim arguement.
criteria Choice of which selection criteria should be used in the algorithm. The choices are either AIC or BIC
delta Delta value used of the BIC is selected. If no value is entered it defaults to 1.
full.output if true the SegList output includes a probability that a clone is in its assigned state and a smoothed value for the clone.
eps parameter controlling the convergence of the EM algorithm.

See Also

runDNAcopy runGLAD SegList


[Package snapCGH version 1.4.0 Index]