# states.hmm.func

0th

Percentile

##### A function to fit unsupervised Hidden Markov model

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

Keywords
models
##### Usage
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.
aCGH