TY - JOUR
T1 - Testing for positive expectation dependence
AU - Zhu, Xuehu
AU - Guo, Xu
AU - Lin, Lu
AU - Zhu, Lixing
N1 - Publisher Copyright:
© 2014, The Institute of Statistical Mathematics, Tokyo.
PY - 2016/2/1
Y1 - 2016/2/1
N2 - In this paper, hypothesis testing for positive first-degree and higher-degree expectation dependence is investigated. Some tests of Kolmogorov–Smirnov type are constructed, which are shown to control type I error well and to be consistent against global alternative hypothesis. Further, the tests can also detect local alternative hypotheses distinct from the null hypothesis at a rate as close to the square root of the sample size as possible, which is the fastest possible rate in hypothesis testing. A nonparametric Monte Carlo test procedure is applied to implement the new tests because both sampling and limiting null distributions are not tractable. Simulation studies and a real data analysis are carried out to illustrate the performances of the new tests.
AB - In this paper, hypothesis testing for positive first-degree and higher-degree expectation dependence is investigated. Some tests of Kolmogorov–Smirnov type are constructed, which are shown to control type I error well and to be consistent against global alternative hypothesis. Further, the tests can also detect local alternative hypotheses distinct from the null hypothesis at a rate as close to the square root of the sample size as possible, which is the fastest possible rate in hypothesis testing. A nonparametric Monte Carlo test procedure is applied to implement the new tests because both sampling and limiting null distributions are not tractable. Simulation studies and a real data analysis are carried out to illustrate the performances of the new tests.
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U2 - 10.1007/s10463-014-0492-7
DO - 10.1007/s10463-014-0492-7
M3 - Article
AN - SCOPUS:84953358440
SN - 0020-3157
VL - 68
SP - 135
EP - 153
JO - Annals of the Institute of Statistical Mathematics
JF - Annals of the Institute of Statistical Mathematics
IS - 1
ER -