JSM 2011 Online Program

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Abstract Details

Activity Number: 304
Type: Contributed
Date/Time: Tuesday, August 2, 2011 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing
Abstract - #301701
Title: Moment Estimation Based on Quantiles
Author(s): Haobo Ren*+ and Weining Shen and Richard Wu and Yuhwen Soo
Companies: Regeneron Pharmaceuticals, Inc. and North Carolina State University and Regeneron Pharmaceuticals, Inc. and Regeneron Pharmaceuticals, Inc.
Address: 400 Somerset Corporate Boulevard, Suite 601, Bridgewater, NJ, 08807,
Keywords: Quantile ; Mean ; Standard Variance ; Generalized Lambda Distribution

Quantiles are the critical characteristics of a distribution and play a fundamental role in statistics. However, under some circumstances, we wish to estimate some moment parameters of a sample, such as mean and variance, based on the given empirical quantiles. For example, we were trying to calculate the sample size of a planned clinical trial to compare two-sample means based on a reference article which only provides key quartiles. This experience encouraged us to formulate it as a research topic. Two contributions toward the solution are reported in this talk, one is the derivation of the range of both mean and standard deviation by an optimization approach, the other is to estimate mean and standard deviation by fitting the generalized lambda distributions of quantiles. We focus on the computational perspective and some examples are illustrated.

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