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.
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