×

zbMATH — the first resource for mathematics

Consistent nonparametric entropy-based testing. (English) Zbl 0719.62055
Summary: The Kullback-Leibler information criterion is used as a basis for one- sided testing of nested hypotheses. No distributional form is assumed, so nonparametric density estimation is used to form the test statistic. In order to obtain a normal null limiting distribution, a form of weighting is employed. The test is also shown to be consistent against a class of alternatives. The exposition focusses on testing for serial independence in time series, with a small application to testing the random walk hypothesis for exchange rate series, and tests of some other hypotheses of econometric interest are briefly described.

MSC:
62G10 Nonparametric hypothesis testing
62G07 Density estimation
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
62P20 Applications of statistics to economics
PDF BibTeX XML Cite
Full Text: DOI