L-moments for data summary and distribution fitting
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Speakers:
Nicholas J. Cox, Durham University, and
Patrick Royston, Imperial College
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The method of L-moments formalised by J.R.M. Hosking offers an elegant and
useful means of summarising and comparing data sets. L-moments are more
resistant to outliers, and for higher moments less biased, than classical
estimators, yet are in many ways less ad hoc than several approaches based
on order statistics. The method is also helpful for fitting various
distributions to data, particularly when maximum likelihood is impractical.
The method will be outlined with a variety of real examples, principally
environmental and medical. The paper will introduce and explain Stata
programs written by the authors.
