RJaCGH (version 1.5.7)

trace.plot: 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. The colors does not correspond to any particular level of gain/loss. A plot is drawn. Rueda OM, Diaz-Uriarte R. Flexible and Accurate Detection of Genomic Copy-Number Changes from aCGH. PLoS Comput Biol. 2007;3(6):e122 [object Object],[object Object]

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

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) 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) models