The Annals of Statistics

Testing that a Gaussian Process is Stationary

T. W. Epps

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Abstract

A class of procedures is proposed for testing the stationarity of a Gaussian process or the homogeneity of independent processes. Requiring very limited prior knowledge of model structure, the methods can detect changes or differences in mean, in variance, in covariances and even in law. Although the theory of the stationarity test is worked out only for processes whose realizations are stationary over "epochs" separated by known change points, Monte Carlo evidence indicates that it can be useful also in detecting more general forms of nonstationarity. The test statistic is a quadratic form in differences among epoch means of certain "sensing" functions, the choice of which governs sensitivity to specific forms of nonstationarity or inhomogeneity. The applicability of the general asymptotic theory of the test is verified for two specific forms of sensing function, and small-sample properties of tests of each form are studied by means of simulation.

Article information

Source
Ann. Statist., Volume 16, Number 4 (1988), 1667-1683.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176351060

Digital Object Identifier
doi:10.1214/aos/1176351060

Mathematical Reviews number (MathSciNet)
MR964945

Zentralblatt MATH identifier
0653.62063

JSTOR
links.jstor.org

Subjects
Primary: 62M99: None of the above, but in this section
Secondary: 60G15: Gaussian processes

Keywords
Chi-squared test empirical characteristic function homogeneity stochastic process time series

Citation

Epps, T. W. Testing that a Gaussian Process is Stationary. Ann. Statist. 16 (1988), no. 4, 1667--1683. doi:10.1214/aos/1176351060. https://projecteuclid.org/euclid.aos/1176351060


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