Some c-sample rank tests of homogeneity against ordered alternatives based on U-statistics
Author:
Wolfgang K
ssler a
ssler a
| Affiliation: | a Institut f r Informatik, Humboldt-Universit t zu Berlin, Berlin, Germany |
DOI:
10.1080/10485250500077254
Publication Frequency:
8 issues per year
Published in:
Journal of Nonparametric Statistics,
Volume
17,
Issue
7
October
2005
, pages 777
- 795
Subjects:
Mathematical Economics;
Mathematical Finance;
Medical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
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Abstract
For the c-sample location problem with ordered alternatives we construct some test statistics, all of them are based on U-statistics. Several statistics from the literature are generalized and extended to our problem. In particular, the statistics of Xie and Priebe [Xie, J. and Priebe, C.E., 2002, A weighted generalization of the Mann-Whitney-Wilcoxon statistic. Journal of Statistical Planning and Inference, 102, 441-466.] are generalized from the two-sample problem. All the corresponding tests are based on different pairwise ranking methods, that of Puri [Puri, M.L., 1965, Some distribution-free k-sample rank tests of homogeneity against ordered alternatives. Communications on Pure and Applied Mathematics, 18, 51-63.], of Tryon and Hettmannsperger [Tryon, P.V. and Hettmansperger, T.P., 1973, A class of nonparametric tests for homogeneity against ordered alternatives. Annals of Statistics, 1, 1061-1070.], and of B
ning and K ssler [B ning, H. and K ssler, W., 1999, The asymptotic power of Jonckheere-type tests for ordered alternatives. Australian and New Zealand Journal of Statistics, 41, 67-77.]. The asymptotic power and the asymptotic relative efficiency are derived. Some of these tests are used to construct adaptive tests. A simulation study shows that the asymptotic results can be used for sample sizes as small as ni = 10.
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| Keywords: Jonckheere-type test; Puri-type test; Tryon-Hettmansperger-type test; Adaptive test; Efficacy; Asymptotic relative efficiency |
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r Informatik, Humboldt-Universit
t zu Berlin, Berlin, Germany
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