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Theory & Methods: A Nonparametric Test for the Parallelism of Two First‐Order Autoregressive Processes
Author(s) -
Guo JiinHuarng
Publication year - 1999
Publication title -
australian and new zealand journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 1369-1473
DOI - 10.1111/1467-842x.00061
Subject(s) - studentized range , mathematics , nonparametric statistics , autoregressive model , statistics , test statistic , statistic , parallelism (grammar) , mann–whitney u test , statistical hypothesis testing , econometrics , computer science , standard error , parallel computing
A nonparametric testing procedure for the parallelism of two first‐order autoregressive processes is presented. This paper discuss the Mann–Whitney statistic, its natural competitor two‐sample t ‐test, and the bootstrap method. It studies the asymptotic efficacies of the studentized Mann–Whitney statistic and the t ‐test statistic with their relative efficiency. Simulation results for comparing the powers of these test statistics are also presented.