FDRSeg (version 1.0-2)

simulQuantile: Quantile simulations

Description

Simulate the quantiles of multiscale statistics for SMUCE, FDRSeg, and D-FDRSeg under null hypothesis.

Usage

simulQuantile(alpha, n, r = round(50/min(alpha, 1-alpha)), 
              type = c("smuce","fdrseg","dfdrseg"), convKern, pos = .GlobalEnv)

Arguments

alpha

a scalar with values in [0, 1]; the alpha-quantile of the null distribution of the multiscale statistic for SMUCE, FDRSeg, or D-FDRSeg via Monte Carlo simulation, see (Frick et al., 2014; Hotz et al., 2013; Li et al., 2015) for an explanation

n

number of observations

r

numer of Monte Carlo simulations

type

"smuce"     simulate quantile for SMUCE
"fdrseg"    simulate quantiles for FDRSeg
"dfdrseg"   simulate quantiles for D-FDRSeg

convKern

convolution kernel, only needed when type is "dfdrseg"

pos

environment for saving the simulations for possible later usage

Value

A scalar value if type is chosen as "smuce"; a numeric vector of length n if type is chosen as "fdrseg" or "dfdrseg".

References

Frick, K., Munk, A., and Sieling, H. (2014). Multiscale Change-Point Inference. J. R. Statist. Soc. B, with discussion and rejoinder by the authors, 76:495--580.

Hotz, T., Schuette, O. M., Sieling, H., Polupanow, T., Diederichsen, U., Steinem, C., and Munk, A. (2013). Idealizing ion channel recordings by a jump segmentation multiresolution filter. IEEE Transactions on Nanobioscience, 12(4):376--86.

Li, H., Munk, A., and Sieling, H. (2015). FDR-control in multiscale change-point segmentation. arXiv:1412.5844.

See Also

smuce, fdrseg, dfdrseg

Examples

# NOT RUN {
library(stepR)

# simulate quantiles for independent Gaussian noises
qs  <- simulQuantile(0.9, 100, type = "smuce")
qfs <- simulQuantile(0.9, 100, type = "fdrseg")
# plot result
yrng <- range(qs, qfs)
plot(qfs, pch = 20, ylim = yrng, xlab = "n", ylab = "")
abline(h = qs)

# simulate  quantiles for dependent Gaussian noises
convKern <- dfilter("bessel")$kern  # create digital filters
qdfs     <- simulQuantile(0.9, 100, type = "dfdrseg", convKern = convKern)
plot(qdfs, pch = 20, xlab = "n", ylab = "")
# }