states.hmm.func: A function to fit unsupervised Hidden Markov model

Description Usage Arguments See Also

View source: R/hmm.R

Description

This function is a workhorse of find.hmm.states. It operates on the individual chromosomes/samples and is not called directly by users.

Usage

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states.hmm.func(sample, chrom, dat, datainfo = clones.info, vr = 0.01,
                maxiter = 100, aic = FALSE, bic = TRUE, delta = 1,
                nlists = 1, eps = .01, print.info = FALSE,
                diag.prob = .99)

Arguments

sample

sample identifier

chrom

chromosome identifier

dat

dataframe with clones in the rows and samples in the columns

datainfo

dataframe containing the clones information that is used to map each clone of the array to a position on the genome. Has to contain columns with names Clone/Chrom/kb containing clone names, chromosomal assignment and kb positions respectively

vr

Initial experimental variance

maxiter

Maximum number of iterations

aic

TRUE or FALSE variable indicating whether or nor AIC criterion should be used for model selection (see DETAILS)

bic

TRUE or FALSE variable indicating whether or nor BIC criterion should be used for model selection (see DETAILS)

delta

numeric vector of penalty factors to use with BIC criterion. If BIC is true, delta=1 is always calculated (see DETAILS)

nlists

defaults to 1 when aic=TRUE, otherwise > 1

eps

parameter controlling the convergence of the EM algorithm.

print.info

print.info = T allows diagnostic information to be printed on the screen.

diag.prob

parameter controlling the construction of the initial transition probability matrix.

See Also

aCGH


Bioconductor-mirror/aCGH documentation built on June 1, 2017, 4:13 a.m.