6533b7dcfe1ef96bd1271f75
RESEARCH PRODUCT
Multivariate Nonparametric Tests
Hannu OjaRonald H. Randlessubject
Statistics and Probabilityeducation.field_of_studyMultivariate statisticsspatial signWilcoxon signed-rank testGeneral MathematicsRank (computer programming)PopulationNonparametric statisticsUnivariaterobustnessSpearman's rank correlation coefficientspatial rankPitman efficiencyStatisticsAffine invarianceEconometricsSign testStatistics::MethodologyStatistics Probability and UncertaintyeducationMathematicsdescription
Multivariate nonparametric statistical tests of hypotheses are described for the one-sample location problem, the several-sample location problem and the problem of testing independence between pairs of vectors. These methods are based on affine-invariant spatial sign and spatial rank vectors. They provide affine-invariant multivariate generalizations of the univariate sign test, signed-rank test, Wilcoxon rank sum test, Kruskal–Wallis test, and the Kendall and Spearman correlation tests. While the emphasis is on tests of hypotheses, certain references to associated affine-equivariant estimators are included. Pitman asymptotic efficiencies demonstrate the excellent performance of these methods, particularly in heavy-tailed population settings. Moreover, these methods are easy to compute for data in common dimensions.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2004-11-01 |