TESTS FOR COMPARING TIME-INVARIANT AND TIME-VARYING SPECTRA BASED ON THE PEARSON STATISTIC

Two tests are proposed in this paper for comparing spectra of two univariate time series. One is a Pearson-like statistic based only on periodograms of the compared time series and applicable for testing the equality of two time-invariant spectra of two independent or dependent time series, with an asymptotic chi-squared distribution under the null hypothesis. The other is based on the maximum of the Pearson-like statistics. Not only does this test, again, depend only on periodograms but also approximately equals the maximum of a chi-squared distribution of the same degrees of freedom under the null. It can be used to test the equality of spectra of two locally stationary time series regardless of whether they are dependent or independent. Multiple simulation examples show that both statistics achieve good performance. The proposed approach is illustrated by an application to longitudinal vibration data from a container ship.