Package: lmomco
Title: L-moments, L-comoments, and Distributions
Version: 0.3
Date: 2006-01-31
Author: William H. Asquith
Description: The package implements the statistical theory of L-moments including
L-moment estimation, probability-weighted moment estimation, parameter estimation
for numerous familiar and not-so-familiar distributions, and L-moment estimation
for the same distributions from the parameters. L-moments are derived from the
expectations of order statistics and are linear with respect to the probability-
weighted moments. L-moments are directly analogous to the well-known product
moments; however, L-moments have many advantages including unbiasedness,
robustness, and consistency with respect to the product moments. This package
is oriented around the FORTRAN algorithms of J.R.M. Hosking, and the
nomenclature for many of the functions parallels that of the Hosking library.
Further features are added to aid in extension of the breadth of L-moment
application. Additionally, recent developments by Robert Serfling and Peng Xiao
have extended L-moments into multivariate space; the so-called sample L-comoments
are implemented here.
Maintainer: William H. Asquith <wasquith@austin.rr.com>
License: GPL
Packaged: Tue Jan 31 14:18:07 2006; wasquith

Package: lmomco
Title: L-moments, L-comoments, Trimmed L-moments, and Distributions
Version: 0.4
Date: 2006-02-28
Author: William H. Asquith
Description: The package implements the statistical theory of L-moments including
L-moment estimation, probability-weighted moment estimation, parameter estimation
for numerous familiar and not-so-familiar distributions, and L-moment estimation
for the same distributions from the parameters. L-moments are derived from the
expectations of order statistics and are linear with respect to the probability-
weighted moments. L-moments are directly analogous to the well-known product
moments; however, L-moments have many advantages including unbiasedness,
robustness, and consistency with respect to the product moments. This package
is oriented around the FORTRAN algorithms of J.R.M. Hosking, and the
nomenclature for many of the functions parallels that of the Hosking library.
Further features are added to aid in extension of the breadth of L-moment
application. Much theoretical extension of L-moment theory has occurred in
recent years. E.A.H. Elamir and A.H. Seheult have developed the trimmed L-moments,
which are implemented in this package. Further, recent developments by Robert
Serfling and Peng Xiao have extended L-moments into multivariate space; the so-called
sample L-comoments are implemented here.
Maintainer: William H. Asquith <wasquith@austin.rr.com>
License: GPL
Packaged: Mon Feb 27 22:40:01 2006; wasquith