Article ID Journal Published Year Pages File Type
1150420 Journal of Statistical Planning and Inference 2009 8 Pages PDF
Abstract

We propose a new nonparametric test to test for symmetry and separability of space–time covariance functions. Unlike the existing nonparametric tests, our test has the attractive convenience of being free of choosing any user-chosen number or smoothing parameter. The asymptotic null distributions of the test statistics are free of nuisance parameters and the critical values have been tabulated in the literature. From a practical point of view, our test is easy to implement and can be readily used by the practitioner. A Monte-Carlo experiment and real data analysis illustrate the finite sample performance of the new test.

Related Topics
Physical Sciences and Engineering Mathematics Applied Mathematics
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