ksTest: Kolmogorov-Smirnov statistics

In genomaths/MethylIT.utils: MethylIT utility

Kolmogorov-Smirnov statistics

Description

Permutation test for Kolmogorov-Smirnov statistics

Usage

ksTest(
  x,
  CDF = "Weibull",
  pars,
  num.sampl = 999,
  sample.size,
  numcores = 1,
  verbose = TRUE,
  ...
)

Arguments

x	numerical vector to perform the goodness of fit
CDF	the name of the cummulative distribution function (CDF)
pars	vector of parameters to evaluate the CDF: 4P GG distribution: c(shape=value, scale=value, mu=value, psi=value) 3P GG distribution: c(shape=value, scale=value, psi=value) 3P Weibull distribution: c(shape=value, scale=value, mu=value) 2P Weibull distribution: c(shape=value, scale=value)
num.sampl	number of elements to be sampled
sample.size	number of permutations. If sample.size < length(x), then the test becomes a Monte Carlo test
numcores	number of cores
verbose	If TRUE, prints the function log to stdout
...	other parameters

Value

gamma distribution CDF

Author(s)

Robersy Sanchez - 02/29/2016

References

Alastair Sanderson. Using R to analyse data statistical and numerical data analysis with R http://www.sr.bham.ac.uk/~ajrs/R/r-analyse_data.html

Examples

num.samples <- 1000
x <- rweibull(num.samples, shape = 1.01, scale = 1.01)
ksTest(x, pars = c(shape = 1, scale = 1))

genomaths/MethylIT.utils documentation built on July 4, 2023, 12:05 a.m.