simnul: Test statistic distribution under independence hypothesis

In subrank: Computes Copula using Ranks and Subsampling

Test statistic distribution under independence hypothesis

Description

Simulates the test statistic, under independence

Usage

simnul(sampsize, dimension, subsampsizes, sampnum,KL=TRUE,nbsafe=5,nthreads=2)

Arguments

sampsize	sample size
dimension	sample dimension
subsampsizes	vector of sub-sample sizes
sampnum	number of samples
KL	if TRUE, returns the Kullback-Leibler divergence with the independent case, if FALSE, the L2 distance. There is no re-normalization, contrary to what happens for simany.
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()

Value

lrs	the distances with independent case
scarcities	the proportions of non-reached vector ranks

Author(s)

Jerome Collet

Examples

library(datasets)
# plot(swiss)
c=corc(swiss,1:3,8)
c
RV=sum(c$cop*log(c$cop),na.rm=TRUE)+3*log(8)
sims=simnul(47,3,8,100)
pvalue=mean(RV<sims$lrs)
pvalue
RV
summary(sims$lrs)

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