Statistical Test for Bivariate Uniformity
Author(s) -
Zhenmin Chen,
Tieyong Hu
Publication year - 2014
Publication title -
advances in statistics
Language(s) - English
Resource type - Journals
eISSN - 2356-6892
pISSN - 2314-8314
DOI - 10.1155/2014/740831
Subject(s) - bivariate analysis , test statistic , statistic , univariate , statistics , test (biology) , statistical hypothesis testing , mathematics , monte carlo method , computer science , algorithm , multivariate statistics , paleontology , biology
The purpose of the multidimension uniformity test is to check whether the underlying probability distribution of a multidimensional population differs from the multidimensional uniform distribution. The multidimensional uniformity test has applications in various fields such as biology, astronomy, and computer science. Such a test, however, has received less attention in the literature compared with the univariate case. A new test statistic for checking multidimensional uniformity is proposed in this paper. Some important properties of the proposed test statistic are discussed. As a special case, the bivariate statistic test is discussed in detail in this paper. The Monte Carlo simulation is used to compare the power of the newly proposed test with the distance-to-boundary test, which is a recently published statistical test for multidimensional uniformity. It has been shown that the test proposed in this paper is more powerful than the distance-to-boundary test in some cases
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