Abstract. Since the classical Kolmogorov-Smirnov (K-S) tests for white noise are completely insensitive to both tails it is difficult in a particular application to detect departure from whiteness. A modified version of the widely used (K-S) test of null hypothesis is constructed, that a given time series is Gaussian white noise, against the alternative hypothesis that the time series contains an added or multiplicative deterministic periodic component of unspecified frequency. The usual K-S test is treated as a special case. The proposed test is more powerful than the ordinary K-S test in detecting extreme (low or high) hidden periodicities. Computational procedures necessary for implementation are given.

Received: May 9, 2012

AMS Subject Classification: 60H40, 62F25, 60G10

Key Words and Phrases: Kolmogorov-Smirnov test, frequency analysis, identification of periodic component, goodness-of-fit test for white noise, periodogram, residuals, Spectrum; Stationary process

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DOI: 10.12732/ijpam.v82i4.2 How to cite this paper?
Source: International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395
Year: 2013
Volume: 82
Issue: 4

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