simany: Test statistic distribution under any hypothesis

In subrank: Computes Copula using Ranks and Subsampling

Test statistic distribution under any hypothesis

Description

Simulates the test statistic, under independence

Usage

simany(sampsize,dimension,subsampsizes,sampnum,nbsafe=5,nthreads=2, fun=NULL, ...)

Arguments

sampsize	sample size
dimension	sample dimension
subsampsizes	vector of sub-sample sizes
sampnum	number of samples
nbsafe	the ratio between the number of sub-samples and the cardinality of the discretized copula.
nthreads	number of number of threads, assumed to be strictly positive. For "full throttle" computations, consider using parallel::detectCores()
fun	the function describing the dependence.
...	optional arguments to fun

Value

lrs	the distances with independent case
lrs2mean	the distances with theoretical value, given dependence fun
scarcities	the proportions of non-reached vector ranks
DistTypes	a recall of the list of the distance types: "KL","L2","L1","APE"

Author(s)

Jerome Collet

Examples

depquad <- function(lon,dd,a)
{
  x <- rnorm(lon)
  y0 <- a*x^2
  y <- y0 + rnorm(lon)
  reste=rnorm((dd-2)*lon)
  return(c(x,y,reste))
}
sims0=simany(101,3,8,50,nbsafe=1)
seuils=apply(sims0$lrs,3,quantile,0.95)
seuils=matrix(ncol=4,nrow=50,seuils,byrow=TRUE)
sims1=simany(101,3,8,50,nbsafe=1,fun=depquad,a=0.5)
apply(sims1$lrs[,1,]>seuils,2,mean)

subrank documentation built on April 6, 2023, 1:11 a.m.