Manuj
Your approach in (2) would work, looking at the source (just type
ks.test) your function will be called with a sorted vector of data
values, i.e. HED(sort(x), ...) where x is a a numeric vector of data
values and ... is the parameters as passed to ks.test

This means your function needs to be able to handle a vector of
inputs.  Look at sapply if this is an issue.

HTH
Schalk Heunis

On Sun, Sep 20, 2009 at 4:21 AM, Manuj Sharma <smanuj1...@yahoo.in> wrote:
>
> I have fitted Hyperexponential distribution (HED) and Hypoexponential 
> distribution (HoED) to two different data sets (of size 1000 numeric values 
> each) using a software package called EMpht.
> I want to use R to perform goodness-of-fit test for the fitted distribution 
> with respect to the empirical CDFs of the data sets using KS test 
> (Kolmogorov-Smirnov test).
> ks.test() function in R takes the first argument as the data set,
> and the second argument as the name of the distribution, followed by the 
> distribution parameter values. In case of the CDFs that are already supported 
> by R, this is simple (for example: ks.test(data_set, "pnorm", mean, sd)).
>
> 1. Can somebody please suggest whether R has in-built support for 
> Hyperexponential and Hypoexponential CDFs
> (they do not appear in the list of distribution given in "An Introduction to 
> R"))?
>
> 2. If I write an R function to compute HED (or HoED) CDF value, can I use 
> that function name as second argument in ks.test()? For example, if I 
> implement an R function named HED_CDF with parameters <parameters...>, will 
> it be correct to use ks.test() as follows:
>     ks.test(data_set, "HED_CDF", <parameters...>)
> Will it give correct result?
>
> - Manuj Sharma
>
>
>
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