| ksTest {MethylIT.utils} | R Documentation |
Permutation test for Kolmogorov-Smirnov statistics
ksTest(x, CDF = "Weibull", pars, num.sampl = 999, sample.size, numcores = 1, verbose = TRUE, ...)
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 |
gamma distribution CDF
Robersy Sanchez - 02/29/2016
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
num.samples <- 1000 x <- rweibull(num.samples, shape = 1.01, scale = 1.01) ksTest(x, pars = c(shape = 1, scale = 1))