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RJaCGH (version 2.0.3)

summary.RJaCGH: Summarizing RJaCGH models

Description

'summary' method for objects of class 'RJaCGH'.

Usage

## S3 method for class 'RJaCGH':
summary(object, array=NULL, Chrom=NULL, 
k = NULL, point.estimator = "median",
quantiles=NULL, \ldots)

Arguments

object
RJaCGH objects
array
vector of names of arrays to summarize. If NULL, all of them.
Chrom
vector of chromosomes to summarize. If NULL, all of them.
k
Model to summarize (i.e., number of hidden states). If NULL, the most visited is taken.
point.estimator
Type of point estimator for mu, sigma.2 and beta. It can be "mean", "median" or "mode".
quantiles
A vector of probabilities for the quantiles of the posterior distribution of means and variances.
...
Additional arguments passed to summary.

Value

  • kFrequencies of the hidden states visited by the sampler.
  • muQuantiles of the posterior distribution of mu
  • sigma.2Quantiles of the posterior distribution of sigma.2
  • betaPoint estimator of beta
  • statInitial distribution of the hidden states.

Details

Depending of the arguments passed, a list with contains sublists can be returned, similarly to RJaCGH and similar objects of the family. The point estimator "mode" is simply the max value obtained in a kernel density estimation through the function density

References

Rueda OM, Diaz-Uriarte R. Flexible and Accurate Detection of Genomic Copy-Number Changes from aCGH. PLoS Comput Biol. 2007;3(6):e122

See Also

RJaCGH, states, modelAveraging, plot.RJaCGH, trace.plot,

Examples

Run this code
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.chrom <- RJaCGH(y=y, Pos=Pos, Chrom=Chrom, model="Chrom",
burnin=10, TOT=100, jump.parameters=jp, k.max = 5)
summary(fit.chrom)

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