where F is the target. This distance (times √n) has an asymptotic distribution that does not depend on n, called the Kolmogorov distribution. After searching for a little while, we could not figure where this distribution was available in R. It had to, since ks.test was returning a p-value. Hopefully correct! So I looked into the ks.test function, which happens not to be entirely programmed in C, and found the line
PVAL <- 1 - if (alternative == "two.sided") .Call(C_pKolmogorov2x, STATISTIC, n)
which means that the Kolmogorov distribution is coded as a C function C_pKolmogorov2x in R. However, I could not call the function myself.
> .Call(C_pKolmogorov2x,.3,4) Error: object 'C_pKolmogorov2x' not found
Hence, as I did not want to recode this distribution cdf, I posted the question on stackoverflow (long time no see!) and got a reply almost immediately as to use the package kolmim. Followed by the extra comment from the same person that calling the C code only required to add the path to its name, as in
> .Call(stats:::C_pKolmogorov2x,STAT=.3,n=4)  0.2292
Filed under: Books, Kids, R, Statistics, University life Tagged: C code, importance sampling, Introducing Monte Carlo Methods with R, kolmim, Kolmogorov-Smirnov distance, R, stackoverflow, Université Paris Dauphine