[R-pkgs] Update for R package KScorrect for K-S goodness-of-fit tests

[Phil Novack-Gottshall]

Greetings,

We wanted to announce v. 1.4.0 of the R package 'KScorrect', which 
carries out the Lilliefors correction to the Kolmogorov-Smirnoff (K-S) 
test for use in (one-sample) goodness-of-fit tests.

Aside from several minor changes, the biggest change is that the Monte 
Carlo algorithm now supports parallel implementation, using the 
platform-independent 'doParallel' and 'foreach' infrastructure. For 
complex distributions (such as Weibull, gamma, and mixture of normals), 
running in parallel can significantly reduce computation time.

It's well-established that it 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.

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-gottshall using ben.edu
  Phone: 630-829-6514
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