An Adaptive Empirical Likelihood Test for Parametric Time Series Regression Models
نویسندگان
چکیده
A test for a parametric regression model against a sequence of local alternative is constructed based on an empirical likelihood test statistic that measures the goodness-of-fit between the parametric model and its nonparametric counterpart. To reduce the dependence of the test on a single smoothing bandwidth, the test is formulated by maximizing a standardized version of the empirical likelihood test statistic over a set of smoothing bandwidths. It is demonstrated that the proposed test is able to distinguish local alternatives from the null hypothesis at an optimal rate.
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تاریخ انتشار 2006