wschisq_utils: Utilities for weighted sums of non-central chi squared random...
In sphunif: Uniformity Tests on the Circle, Sphere, and Hypersphere

wschisq_utils

R Documentation

Utilities for weighted sums of non-central chi squared random variables

Description

Simulation from a weighted sum of non-central chi squared random variables and Monte Carlo approximation of its distribution function.

Usage

r_wschisq_Cpp(n, weights, dfs, ncps)

p_wschisq_MC(x, weights = 0L, dfs = 0L, ncps = 0L, M = 10000L,
  sample = 0L, use_sample = FALSE, x_sorted = FALSE)

Arguments

`n`	sample size.
`weights`	vector with the positive weights of the sum. Must have the same length as `dfs`.
`dfs`	vector with the positive degrees of freedom of the chi squared random variables. Must have the same length as `weights`.
`ncps`	non-negative non-centrality parameters. A vector with the same length as `weights`.
`x`	vector of quantiles.
`M`	number of Monte Carlo samples for approximating the distribution. Defaults to `1e4`.
`sample`	if `use_sample = TRUE`, the Monte Carlo sample to approximate the distribution. If not, it is computed internally. Defaults to `1e4`.
`use_sample`	use the already computed `sample`? If `FALSE` (default), `sample` is computed internally.

Value

r_wschisq_Cpp: a matrix of size c(n, 1) containing a random sample.
p_wschisq_MC: a matrix of size c(nx, 1) with the evaluation of the distribution function at x.