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Moment estimation based on quantiles
Author(s) -
Ren Haobo,
Shen Weining,
Wu Richard,
Soo Yuhwen
Publication year - 2013
Publication title -
wiley interdisciplinary reviews: computational statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.693
H-Index - 38
eISSN - 1939-0068
pISSN - 1939-5108
DOI - 10.1002/wics.1267
Subject(s) - quantile , quartile , range (aeronautics) , moment (physics) , mathematics , statistics , variance (accounting) , estimation , distribution (mathematics) , second moment of area , computer science , econometrics , algorithm , mathematical analysis , confidence interval , engineering , physics , accounting , systems engineering , business , aerospace engineering , geometry , classical mechanics
We consider a moment estimation problem using empirical quantiles of the data. Specifically, we estimate the sample mean and the variance based only on the minimum, the quartiles, the median and the maximum values of the data. We propose a computational solution based on fitting a refined version of a generalized λ distribution. Simulation results suggest that our method works reasonably well for a wide range of distributions. WIREs Comput Stat 2013. doi: 10.1002/wics.1267 This article is categorized under: Applications of Computational Statistics > Computational Mathematics