Premium
Non‐Parametric Change‐Point Tests for Long‐Range Dependent Data
Author(s) -
DEHLING HEROLD,
ROOCH AENEAS,
TAQQU MURAD S.
Publication year - 2013
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/j.1467-9469.2012.00799.x
Subject(s) - mathematics , test statistic , sign test , statistics , range (aeronautics) , wilcoxon signed rank test , parametric statistics , null hypothesis , null distribution , statistic , sample size determination , test (biology) , z test , statistical hypothesis testing , gaussian , goldfeld–quandt test , mann–whitney u test , paleontology , materials science , physics , quantum mechanics , composite material , biology
. We propose a non‐parametric change‐point test for long‐range dependent data, which is based on the Wilcoxon two‐sample test. We derive the asymptotic distribution of the test statistic under the null hypothesis that no change occurred. In a simulation study, we compare the power of our test with the power of a test which is based on differences of means. The results of the simulation study show that in the case of Gaussian data, our test has only slightly smaller power minus.3pt than the ‘difference‐of‐means’ test. For heavy‐tailed data, our test outperforms the ‘difference‐of‐means’ test.