trace.plot {RJaCGH}R Documentation

Trace plot for 'RJaCGH' object

Description

A trace plot with the trajectory of the Markov Chain.

Usage

trace.plot(obj, k = NULL, array = NULL, Chrom = NULL, main.text = NULL)

Arguments

obj any of RJaCGH, RJaCGH.Chrom, RJaCGH.genome, RJaCGH.array objects
k Model to plot (i.e., number of hidden states). If NULL, the most visited is taken.
array if obj is 'RJaCGH.array', the name of the array to plot must be given.
Chrom if obj is 'RJaCGH.Chrom', the number of the chromosome to plot must be given.
main.text Main text of the plot

Details

This is simply a call to matplot to show the values sampled in the chain. newline The colors does not correspond to any particular level of gain/loss.

Value

A plot is drawn.

Author(s)

Oscar M. Rueda and Ramon Diaz

References

Oscar M. Rueda and Ramon Diaz Uriarte. A flexible, accurate and extensible statistical method for detecting genomic copy-number changes. http://biostats.bepress.com/cobra/ps/art9/. {http://biostats.bepress.com/cobra/ps/art9/}.

See Also

RJaCGH, summary.RJaCGH, model.averaging, plot.RJaCGH, states, gelman.brooks.plot, collapseChain

Examples

y <- c(rnorm(100, 0, 1), rnorm(10, -3, 1), rnorm(20, 3, 1), rnorm(100,
0, 1))
Pos <- sample(x=1:500, size=230, replace=TRUE)
Pos <- cumsum(Pos)
Chrom <- rep(1:23, rep(10, 23))
jp <- list(sigma.tau.mu=rep(0.5, 5), sigma.tau.sigma.2=rep(0.3, 5),
sigma.tau.beta=rep(0.7, 5), tau.split.mu=0.5, tau.split.beta=0.5)
fit.genome <- RJaCGH(y=y, Pos=Pos, Chrom=Chrom, model="genome",
burnin=10, TOT=100, jump.parameters=jp, k.max = 5)
trace.plot(fit.genome)

[Package RJaCGH version 1.0.2 Index]