hybrid_power: Power Estimation for the multivariate goodness-of-fit problem...

In MDgof: Various Methods for the Goodness-of-Fit Problem in D>1 Dimensions

Power Estimation for the multivariate goodness-of-fit problem via twosample tests

Description

This function estimates the power of goodness-of-fit/two-sample hybrid tests using Rcpp and parallel computing by generating a Monte Carlo data set and then running a twosample test.

Usage

hybrid_power(
  rnull,
  ralt,
  param_alt,
  phat = function(x) -99,
  nMC = 1,
  TS,
  TSextra,
  With.p.value = FALSE,
  alpha = 0.05,
  B = 1000,
  maxProcessor,
  doMethods = "all"
)

Arguments

rnull	routine to generate data under the null hypothesis.
ralt	routine to generate data under the alternative hypothesis.
param_alt	values passed to ralt.
phat	=function(x) -99 parameter estimation, if needed.
nMC	=1 sample size of Monte Carlo data set, if it is a number nMC<=10 sample size used will be nMC*sample size of x.
TS	user supplied function to find test statistics, if any.
TSextra	(optional) list passed to TS, if needed.
With.p.value	=FALSE, does user supplied method find its own p-values?
alpha	=0.05 type I error rate used in tests.
B	=5000 number of simulation runs. If B=0 the routine returns the test statistics.
maxProcessor	number of processors to use in parallel processing.
doMethods	="all", a vector of codes for the methods to include or all of them.

Details

For details on the usage of this routine consult the vignette with vignette("MDgof-hybrid","MDgof-hybrid")

Value

A list with vectors of test statistics and p.values

Examples

# All examples are run with B=20 and maxProcessor=1 to pass CRAN checks.
# Power of tests see whether data comes from a bivariate standard normal distribution, 
# without parameter estimation. True Distribution is bivariate normal with
# correlation r.
rnull=function() mvtnorm::rmvnorm(100, c(0, 0))
ralt=function(r) mvtnorm::rmvnorm(100, sigma=matrix(c(1,r,r,1),2,2))
hybrid_power(rnull, ralt, 0.3, B=20, maxProcessor = 1)
# Power of tests to see whether data comes from a standard normal distribution, 
# with mean parameter estimated. True data comes from t distribution.
rnull=function(p) mvtnorm::rmvnorm(100, p)
ralt=function(df) mvtnorm::rmvt(100, df=df)
phat=function(x) apply(x, 2, mean)  
hybrid_power(rnull, ralt, 5, phat, B=20, maxProcessor = 1)

MDgof documentation built on Feb. 13, 2026, 1:06 a.m.