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Investigation and comparison of sampling properties of L-moments and conventional moments
 

Summary: Investigation and comparison of sampling properties of L-moments
and conventional moments
A. Sankarasubramanian1
, K. Srinivasan*
Department of Civil Engineering, Indian Institute of Technology Madras, Chennai 600 036, India
Received 3 December 1997; accepted 26 January 1999
Abstract
The first part of this article deals with fitting of regression equations for the sampling properties, variance of L-standard
deviation (l2), and bias and variance of L-skewness (t3), based on Monte-Carlo simulation results, for generalised Normal
(Lognormal-3) and Pearson-3 distributions. These fitted equations will be useful in formulating goodness-of-fit test statistics in
regional frequency analysis. The second part presents a comparison of the sampling properties between L-moments and
conventional product moments for generalised Normal, generalised Extreme Value, generalised Pareto and Pearson-3 distribu-
tions, in a relative form. The comparison reveals that the bias in L-skewness is found to be insignificant up to a skewness of
about 1.0, even for small samples. In case of higher skewness, for a reasonable sample size of 30, L-skewness is found to be
nearly unbiased. However, the conventional skewness is found to be significantly biased, even for a low skewness of 0.5 and a
reasonable sample size of 30. The overall performance evaluation in terms of "Relative-RMSE in third moment ratio" reveals
that conventional moments are preferable at lower skewness, particularly for smaller samples, while L-moments are preferable
at higher skewness, for all sample sizes. This point is illustrated through an application that seeks to obtain an appropriate
regional flood frequency distribution for the 98 catchment areas located in the central region of India, spread over six
hydrometeorologic subzones. 1999 Elsevier Science B.V. All rights reserved.

  

Source: Arumugam, Sankar - Department of Civil, Construction, and Environmental Engineering, North Carolina State University

 

Collections: Environmental Sciences and Ecology; Engineering