Object of class 'Les' as returned by 'estimate' or
'regions'.
subset
Vector of logical specifying the probes for which the CIs
should be computed. If missing CIs will be computed for all probes.
nBoot
Integer specifying the number of bootstrap samples
(default: 100). For details see 'boot' from the 'boot' package.
conf
Numeric specifying the confidence level (default:
0.95). For details see 'boot' from the 'boot' package.
nCores
Integer indicating the number of cores to use for
computation. This feature requires the 'multicore' package which
is only available for certain platforms. The package is used only if
'library(multicore)' has been called manually by the user before and if
'nCores' is an integer unequal NULL specifying the number of cores
to use. The value is passed directly to 'mclapply' as argument
'n.cores'. For details and benefits please see the 'Details'
section.
...
Further arguments passed to subsequent functions.
Details
The 'ci' method computes confidence intervals (CI) by bootstrapping
probes in each window. Since based on percentiles the resulting CIs
are asymmetrical.
All arguments for computation are taken from 'object' and thereby kept
the same as for the results from 'estimation'.
Since bootstrapping is computational demanding and CIs are often only
wanted for certain regions of interest it may be useful to restrict
computation with the 'subset' argument.
The 'multicore' package can be used to spread the computation over several
cores in a simple way. This can be useful on multi-core machines for
large datasets or computation of confidence intervals for many
probes. The 'multicore' package is not available on all platforms. To
use multicore processing 'library(multicore)' has to be called
beforehand and a number of cores to use has to be specified in
'nCores'. For details see the documentation of the 'multicore' package.
Value
Object of class 'Les' with additionally filled slots:
ci, subset, nBoot, conf
Methods and functions:
Lesestimatethresholdregionscichi2exportplot
Examples
data(spikeInStat)
x <- Les(pos, pval)
x <- estimate(x, win=200, grenander=FALSE)
subset <- pos >= 5232300 & pos <= 5233200
x <- ci(x, subset, conf=0.90, nBoot=50)
plot(x, error="ci")
## Not run:
## multicore computation
## only available on certain platforms
library(multicore)
x <- ci(x, subset=150:200, conf=0.90, nBoot=50, nCores=2)
## End(Not run)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(les)
Loading required package: fdrtool
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/les/ci.Rd_%03d_medium.png", width=480, height=480)
> ### Name: ci,Les-method
> ### Title: ci
> ### Aliases: ci ci-methods ci,Les ci,Les-method
> ### Keywords: htest methods
>
> ### ** Examples
>
> data(spikeInStat)
>
> x <- Les(pos, pval)
> x <- estimate(x, win=200, grenander=FALSE)
>
> subset <- pos >= 5232300 & pos <= 5233200
> x <- ci(x, subset, conf=0.90, nBoot=50)
>
> plot(x, error="ci")
>
> ## Not run:
> ##D ## multicore computation
> ##D ## only available on certain platforms
> ##D library(multicore)
> ##D x <- ci(x, subset=150:200, conf=0.90, nBoot=50, nCores=2)
> ## End(Not run)
>
>
>
>
>
> dev.off()
null device
1
>