Open Access
August 2014 Comparison of multivariate distributions using quantile–quantile plots and related tests
Subhra Sankar Dhar, Biman Chakraborty, Probal Chaudhuri
Bernoulli 20(3): 1484-1506 (August 2014). DOI: 10.3150/13-BEJ530

Abstract

The univariate quantile–quantile (Q–Q) plot is a well-known graphical tool for examining whether two data sets are generated from the same distribution or not. It is also used to determine how well a specified probability distribution fits a given sample. In this article, we develop and study a multivariate version of the Q–Q plot based on the spatial quantile. The usefulness of the proposed graphical device is illustrated on different real and simulated data, some of which have fairly large dimensions. We also develop certain statistical tests that are related to the proposed multivariate Q–Q plot and study their asymptotic properties. The performance of those tests are compared with that of some other well-known tests for multivariate distributions available in the literature.

Citation

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Subhra Sankar Dhar. Biman Chakraborty. Probal Chaudhuri. "Comparison of multivariate distributions using quantile–quantile plots and related tests." Bernoulli 20 (3) 1484 - 1506, August 2014. https://doi.org/10.3150/13-BEJ530

Information

Published: August 2014
First available in Project Euclid: 11 June 2014

zbMATH: 06327916
MathSciNet: MR3217451
Digital Object Identifier: 10.3150/13-BEJ530

Keywords: characterization of distributions , contiguous alternatives , Gaussian process , Pitman efficacy , spatial quantiles , tests for distributions , the level and the power of test

Rights: Copyright © 2014 Bernoulli Society for Mathematical Statistics and Probability

Vol.20 • No. 3 • August 2014
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