Open Access
November 2004 Quantile Probability and Statistical Data Modeling
Emanuel Parzen
Statist. Sci. 19(4): 652-662 (November 2004). DOI: 10.1214/088342304000000387

Abstract

Quantile and conditional quantile statistical thinking, as I have innovated it in my research since 1976, is outlined in this comprehensive survey and introductory course in quantile data analysis. We propose that a unification of the theory and practice of statistical methods of data modeling may be possible by a quantile perspective. Our broad range of topics of univariate and bivariate probability and statistics are best summarized by the key words. Two fascinating practical examples are given that involve positive mean and negative median investment returns, and the relationship between radon concentration and cancer.

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Emanuel Parzen. "Quantile Probability and Statistical Data Modeling." Statist. Sci. 19 (4) 652 - 662, November 2004. https://doi.org/10.1214/088342304000000387

Information

Published: November 2004
First available in Project Euclid: 18 April 2005

zbMATH: 1100.62500
MathSciNet: MR2185587
Digital Object Identifier: 10.1214/088342304000000387

Keywords: Bayesian inference using quantile simulation , bivariate dependence , comparison density , comparison distribution , component correlations , Conditional quantile , confidence Q–Q curve , density quantile , Mid-distribution transform , monotone transform , parameter inverse pivot quantile function , percent function , percentile function , quantile density , quantile function , quantile–quartile function QIQ(u)

Rights: Copyright © 2004 Institute of Mathematical Statistics

Vol.19 • No. 4 • November 2004
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