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Tests of serial independence based on Kendall's process
Author(s) -
Genest Christian,
Quessy JeanFranÇlois,
RÉamillard Bruno
Publication year - 2002
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.2307/3316147
Subject(s) - autocorrelation , statistics , mathematics , white noise , series (stratigraphy) , independence (probability theory) , null hypothesis , statistical hypothesis testing , rank (graph theory) , noise (video) , empirical distribution function , econometrics , computer science , artificial intelligence , combinatorics , paleontology , image (mathematics) , biology
The authors propose new rank statistics for testing the white noise hypothesis in a time series. These statistics are Cramér‐von Mises and Kolmogorov‐Smirnov functionals of an empirical distribution function whose mean is related to a serial version of Kendall's tau through a linear transform. The authors determine the asymptotic behaviour of the underlying serial process and the large‐sample distribution of the proposed statistics under the null hypothesis of white noise. They also present simulation results showing the power of their tests.