twosample_test: Tests for the univariate two-sample problem

In R2sample: Various Methods for the Two Sample Problem

Tests for the univariate two-sample problem

Description

This function runs a number of two sample tests using Rcpp and parallel computing.

Usage

twosample_test(
  x,
  y,
  vals = NA,
  TS,
  TSextra,
  wx = rep(1, length(x)),
  wy = rep(1, length(y)),
  B = 5000,
  nbins = c(50, 10),
  minexpcount = 5,
  maxProcessor,
  UseLargeSample,
  samplingmethod = "Binomial",
  rnull,
  SuppressMessages = FALSE,
  doMethods = "all"
)

Arguments

x	a vector of numbers if data is continuous or of counts if data is discrete or a list with the data
y	a vector of numbers if data is continuous or of counts if data is discrete.
vals	=NA, a vector of numbers, the values of a discrete random variable. NA if data is continuous data.
TS	routine to calculate test statistics for non-chi-square tests
TSextra	additional info passed to TS, if necessary
wx	A numeric vector of weights of x.
wy	A numeric vector of weights of y.
B	=5000, number of simulation runs for permutation test
nbins	=c(50,10), number of bins for chi square tests.
minexpcount	=5, minimum required expected counts for chi-square tests.
maxProcessor	maximum number of cores to use. If missing (the default) no parallel processing is used.
UseLargeSample	should p values be found via large sample theory if n,m>10000?
samplingmethod	="Binomial" or "independence" for discrete data
rnull	a function that generates data from a model, possibly with parameter estimation.
SuppressMessages	= FALSE print informative messages?
doMethods	="all" a vector of codes for the methods to include. If "all", all methods are used.

Details

For details consult vignette("R2sample","R2sample")

Value

A list of two numeric vectors, the test statistics and the p values.

Examples

 R2sample::twosample_test(rnorm(1000), rt(1000, 4), B=1000)
 myTS=function(x,y) {z=c(mean(x)-mean(y),sd(x)-sd(y));names(z)=c("M","S");z}
 R2sample::twosample_test(rnorm(1000), rt(1000, 4), TS=myTS, B=1000)
 vals=1:5
 x=table(sample(vals, size=100, replace=TRUE))
 y=table(sample(vals, size=100, replace=TRUE, prob=c(1,1,3,1,1)))
 R2sample::twosample_test(x, y, vals)

R2sample documentation built on June 17, 2025, 1:07 a.m.