README
The analysis of univariate distributions is a complex subject. This
is particularly the case with heavy-tailed data. The L-moments,
which have similar meaning as the ordinary (product or central) moments,
have revolutionized many fields including statistical hydrology in which
your author operates. L-moments have many properties that make them
extremely attractive. These properties include unbiasedness, efficiency,
consistency, robustness, and others. The R package contained here fully
implements L-moments in the context of many probability distributions
including the:
Asymmetric Exponential Power distribution (or Asymmetrical Exponential Power distribution),
Cauchy distribution,
Exponential distribution,
Gamma distribution,
Gumbel distribution,
Generalized Extreme Value distribution,
Generalized Lambda distribution,
Generalized Logistic distribution,
Generalized Normal (log-Normal) distribution,
Govindarajulu distribution,
Generalized Pareto distribution,
Kappa distribution,
Kumaraswamy distribution,
Laplace distribution,
3-parameter log-Normal distribution,
Normal, Pearson Type III distribution,
Slash distribution,
3-parameter Student T distribution,
Rayleigh distribution,
Rice distribution,
Wakeby distribution, and
Weibull distribution.
This package provides core functions and numerous ancillary functions to
help get the user started and to keep the user entertained by building complex
analysis applications. Very recent and extremely exciting developments have
extended L-moments to multi-variate analysis---the sample L-comoments are
implemented here on an experimental basis. The package also implements the
trimmed L-moments and support for the Cauchy, Generalized Lambda, and
Generalized Pareto distributions.
See my monograph on L-moments available at a near zero-royalty price at
http://www.amazon.com/Distributional-Statistics-Environment-Statistical-Computing/dp/1463508417/
wha (March 5, 2014)
See inst/doc/WARRANTY for lack-of-warranty information.
See the excellent R-package Lmoments by Juha Karvanen.
See the excellent R-package lmoms by J.R.M. Hosking.
Note: This is a large package with hundreds of examples. The examples will
take considerable time to process on 'R CMD check lmomco'.
Note: Building binaries on MacOSX or the *.tgz files is accomplished by
R CMD install --build lmomco