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#'@title Function used to perform parallel computing for pseudo-observations of generalized Ornstein-Uhlenbeck
#'
#'@description This function simulates values of the Cramer-von Mises and Kolmogorov-Smirnov statistics for testing goodness-of-fit of GOU.
#'
#'@param n number of simulated points.
#'
#'@return \item{out}{List of gof statistics for GOU: ks (Kolmogorov-Smirnov) and cvm ( Cramer-von Mises)}
#'
#'@keywords internal
#'
#'@export
#'
#'
funGoF <- function(n)
{
eps = rnorm(n)
m = mean(eps)
s = sqrt(var(eps))
u = sort(pnorm((eps-m)/s))
sn = sqrt(n)
tt0=c(1:n)/n
tt = tt0-0.5/n
cvm = 1/(12*n)+ sum((u-tt)^2)
ks=sn*max(abs(u-tt0),abs(u-tt0+1/n))
out=list(cvm=cvm,ks=ks)
out
}
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