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March, 1977 A Test for Serial Correlation in Multivariate Data
Walter S. Liggett Jr.
Ann. Statist. 5(2): 408-413 (March, 1977). DOI: 10.1214/aos/1176343808

Abstract

Consider a sample from a multiple time series that is stationary and Gaussian. A test is presented for independence among the multivariate observations that comprise this sample. The test is a generalization of the Kolmogorov-Smirnov test for serial correlation in a single time series. In the test, pairs of spectral-matrix estimates are compared using the largest-root statistic. The comparisons, which are tested simultaneously, are between estimates obtained from upper and lower parts of the frequency band. Under the null hypothesis, the joint distribution of the largest roots is obtained in a form suitable for computation of significance levels.

Citation

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Walter S. Liggett Jr.. "A Test for Serial Correlation in Multivariate Data." Ann. Statist. 5 (2) 408 - 413, March, 1977. https://doi.org/10.1214/aos/1176343808

Information

Published: March, 1977
First available in Project Euclid: 12 April 2007

zbMATH: 0358.62063
MathSciNet: MR431567
Digital Object Identifier: 10.1214/aos/1176343808

Subjects:
Primary: 62M15
Secondary: 62H15

Rights: Copyright © 1977 Institute of Mathematical Statistics

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Vol.5 • No. 2 • March, 1977
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