Comparison of multivariate distributions using quantile-quantile plots and related tests

Subhra Sankar Dhar, Biman Chakraborty, Probal Chaudhuri

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)1484-1506
JournalBernoulli
Volume20
Issue number3
DOIs
Publication statusPublished - 4 Jul 2014

Bibliographical note

Published in at http://dx.doi.org/10.3150/13-BEJ530 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)

Keywords

  • math.ST
  • stat.TH

Fingerprint

Dive into the research topics of 'Comparison of multivariate distributions using quantile-quantile plots and related tests'. Together they form a unique fingerprint.

Cite this