Greetings,

We wanted to announce a new R package 'KScorrect' that carries out the 
Lilliefors correction to the Kolmogorov-Smirnoff test for use in (one-sample) 
goodness-of-fit tests.

It's well-established it's inappropriate to use the K-S test when sample 
statistics are used to estimate parameters, which results in substantially 
increased Type-II errors. This warning is mentioned in the ks.test Help page, 
but no general solution is currently available for non-normal distributions.

The 'KScorrect' package corrects for the bias by using Monte Carlo simulation, 
a solution first recommended by Lilliefors (1967) but not widely heeded. The 
primary function 'LcKS()' is written to complement, and can be used directly in 
place of, 'ks.test()'. It can be used with most continuous distribution 
functions, including normal, univariate mixture of normals, lognormal, uniform, 
loguniform (flat when data are log-transformed), exponential, gamma, and 
Weibull distributions, and corresponding maximum-likelihood parameters are 
estimated automatically from the provided sample.

Distribution functions are provided in the package for the loguniform and 
univariate mixture of normal distributions, which are not included in the R 
base installation.

Simple examples are provided by calling example(KScorrect) or example(LcKS).

Additional details are available at 
https://cran.r-project.org/web/packages/KScorrect. Bug reports, suggestions, 
and feature requests are encouraged at 
https://github.com/pnovack-gottshall/KScorrect. 

We hope you find the functions useful when conducting goodness-of-fit tests 
using the K-S test.

Sincerely,
Phil Novack-Gottshall and Steve Wang

-- 
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 Phil Novack-Gottshall
 Associate Professor
 Department of Biological Sciences
 Benedictine University
 5700 College Road 
 Lisle, IL 60532

 pnovack-gottsh...@ben.edu
 Phone: 630-829-6514
 Fax: 630-829-6547
 Office: 332 Birck Hall
 Lab: 316 Birck Hall
 http://www.ben.edu/faculty/pnovack-gottshall
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~


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