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 Exponential, Gamma, Gumbel, Generalized Extreme Value, 
Generalized Lambda, Generalized Logistic, Generalized Normal (log-Normal),
Generalized Pareto, Kappa, Kumaraswamy, Normal, Pearson Type III,
Rayleigh, Rice, Wakeby, and Weibull.

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 zero-royalty price at
http://www.amazon.com/Distributional-Statistics-Environment-Statistical-Computing/dp/1463508417/

wha (June 24, 2011)

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'.
