gelman.brooks.plot {RJaCGH}R Documentation

gelman-brooks plot for 'RJaCGH' objects

Description

A plot to show the convergence of several parallel chains, as described in Brooks and Gelman, 1998.

Usage

gelman.brooks.plot(obj, bin = 1000, array = NULL, Chrom = NULL, k = NULL)

Arguments

obj a list containing several parallel chains; that is objects of any of RJaCGH, RJaCGH.Chrom, RJaCGH.genome, RJaCGH.array classes (obviously, all of the same class).
bin Number of observations taken in every subchain
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.
k Model to monitorize (i.e., number of hidden states). If NULL, the most visited is taken.

Details

As described in the references, for every bin runs of the chain, the R value of k, mu, sigma.2 and beta are computed.

Value

A plot showing the R values is drawn. Besides, a list is returned with components

k R values for the numebr of states
mu R values for the means of the states
mu R values for the variances of the states
mu R values for the beta parameters

Author(s)

Oscar Rueda and Ramon Diaz Uriarte

References

Brooks, S.P. and Gelman, A. (1998). General Methods for Monitoring convergence of iterative simulations. Journal of Computational and Graphical Statistics. p434-455.

Oscar Rueda and Ramon Diaz Uriarte, in prep.

See Also

RJaCGH, summary.RJaCGH, model.averaging, plot.RJaCGH, states, trace.plot, collapseChain

Examples

y <- c(rnorm(100, 0, 1), rnorm(10, -3, 1), rnorm(20, 3, 1),
       rnorm(100,0, 1)) 
Pos <- runif(230)
Pos <- cumsum(Pos)
Chrom <- rep(1:23, rep(10, 23))

jp <- list(sigma.tau.mu=rep(0.5, 4), sigma.tau.sigma.2=rep(0.3, 4),
           sigma.tau.beta=rep(0.7, 4), tau.split.mu=0.5, tau.split.beta=0.5)

fit.genome <- list()
for (i in 1:4) {
fit.genome[[i]] <- RJaCGH(y=y, Pos=Pos, Chrom=Chrom, model="genome",
burnin=10, TOT=1000, jump.parameters=jp, k.max = 4)
}

## Not run: gelman.brooks.plot(fit.genome)

[Package RJaCGH version 0.4 Index]