Hi, I was recently looking at the fOptions package and I was wondering if anyone knows why the authors of the package bothered to write functions for CND and NDF, when they exist as pnorm and dnorm? I realize there's the possibility that pnorm and dnorm may not have existed when fOptions was written. Regardless, I was wondering it there's some non-obvious advantage to using CND or NDF versus the base stats functions. If anything, from http://svn.r-project.org/R/trunk/src/nmath/pnorm.c it sounds like pnorm could be slightly more accurate.
"This transportable program uses rational functions that theoretically approximate the normal distribution function to at least 18 significant decimal digits. The accuracy achieved depends on the arithmetic system, the compiler, the intrinsic functions, and proper selection of the machine-dependent constants." They seem to basically return the same values plus or minus some extremely small floating point error. library(fOptions) > x <- seq(-4, 4, 0.01) > all.equal(pnorm(x), CND(x)) [1] "Mean relative difference: 8.845649e-08" > all.equal(dnorm(x), NDF(x)) [1] TRUE Thanks, James [[alternative HTML version deleted]] _______________________________________________ R-SIG-Finance@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go.