RJaCGH (version 1.1.1)

summary.RJaCGH: Summarizing RJaCGH models

Description

'summary' method for objects of class 'RJaCGH', 'RJaCGH.Chrom', 'RJaCGH.genome' and 'RJaCGH.array'.

Usage

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

Arguments

object

any of RJaCGH, RJaCGH.Chrom, RJaCGH.genome, RJaCGH.array objects

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".

...

Additional arguments passed to summary.

Value

• y
  y values
• x
  x values (distances between genes)
• mu
  Point estimator of mu
• sigma.2
  Point estimator of sigma.2
• beta
  Point estimator of beta

Details

Depending of the type of object, 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

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, states, model.averaging, plot.RJaCGH, trace.plot, 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.chrom <- RJaCGH(y=y, Pos=Pos, Chrom=Chrom, model="Chrom",
burnin=10, TOT=100, jump.parameters=jp, k.max = 5)
summary(fit.chrom)