Package: lmomco
Title: L-moments, Trimmed L-moments, L-comoments, and Many
Distributions
Version: 1.2.1
Depends: R (>= 2.7.0), utils
Date: 2010-11-20
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; choice of either
can be made by mathematical convenience. 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. The method of
L-moments can out perform the method of maximum likelihood. The
lmomco package historically is oriented around canonical
FORTRAN algorithms of J.R.M. Hosking, and the nomenclature for
many of the functions parallels that of the Hosking library,
which later became available in the lmom package. However, vast
arrays of various extensions and curiosities are made by the
author to aid and expand of the breadth of L-moment
application. Such extensions venerable statistics as Sen
weighted mean, Gini mean difference, plotting positions, and
conditional probability adjustment. Much extension of L-moment
theory has occurred in recent years, including extension of
L-moments into right-tail censoring conditions by known
censoring threshold or by an indicator variable. Extension to
left-tail censoring is readily made by variable flipping,
treatment as right-tail censored, and finally back-flipping
(re-transformation). E.A.H. Elamir and A.H. Seheult have
developed the trimmed L-moments, which are implemented in this
package. Further, Robert Serfling and Peng Xiao have extended
L-moments into multivariate space; the so-called sample
L-comoments are implemented here and might have considerable
application in copula theory because they measure asymmetric
correlation and higher co-moments. The supported distributions
with moment type shown as L (L-moments) or TL (trimmed
L-moments) and additional support for right-tail censoring
([RC]) include: Cauchy (TL), Exponential (L), Gamma (L),
Generalized Extreme Value (L), Generalized Lambda (L & TL),
Generalized Logistic (L), Generalized Normal (L), Generalized
Pareto (L[RC] & TL), Gumbel (L), Kappa (L), Kumaraswamy (L),
Normal (L), 3-parameter log-Normal (L), Pearson Type III (L),
Rayleigh (L), Reverse Gumbel (L[RC]), Rice (L), Wakeby (L), and
Weibull (L).
Maintainer: William H. Asquith <william.asquith@ttu.edu>
License: GPL
Packaged: 2010-11-21 20:38:26 UTC; wasquith
Repository: CRAN
Date/Publication: 2010-11-22 07:50:47