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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.

62G10 Nonparametric hypothesis testing
62G07 Density estimation
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
62P20 Applications of statistics to economics
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