Moment estimation based on quantiles

Haobo Ren; Weining Shen; Richard Wu; Yuhwen Soo

doi:10.1002/wics.1267

Moment estimation based on quantiles

Haobo Ren, Weining Shen, Richard Wu, Yuhwen Soo

Biostatistics

Research output: Contribution to journal › Review article › peer-review

2 Scopus citations

Abstract

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.

Original language	English (US)
Pages (from-to)	387-390
Number of pages	4
Journal	Wiley Interdisciplinary Reviews: Computational Statistics
Volume	5
Issue number	5
DOIs	https://doi.org/10.1002/wics.1267
State	Published - Sep 2013

Keywords

Generalized λ distribution
Moment estimation
Quantile

ASJC Scopus subject areas

Statistics and Probability

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10.1002/wics.1267

Cite this

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title = "Moment estimation based on quantiles",

abstract = "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.",

keywords = "Generalized λ distribution, Moment estimation, Quantile",

author = "Haobo Ren and Weining Shen and Richard Wu and Yuhwen Soo",

year = "2013",

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T1 - Moment estimation based on quantiles

AU - Ren, Haobo

AU - Shen, Weining

AU - Wu, Richard

AU - Soo, Yuhwen

PY - 2013/9

Y1 - 2013/9

N2 - 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.

AB - 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.

KW - Generalized λ distribution

KW - Moment estimation

KW - Quantile

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U2 - 10.1002/wics.1267

DO - 10.1002/wics.1267

M3 - Review article

AN - SCOPUS:84882861755

SN - 1939-5108

VL - 5

SP - 387

EP - 390

JO - Wiley Interdisciplinary Reviews: Computational Statistics

JF - Wiley Interdisciplinary Reviews: Computational Statistics

IS - 5

ER -

Moment estimation based on quantiles

Abstract

Keywords

ASJC Scopus subject areas

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