Estimation of the Density and the Regression Function under Mixing Conditions Preprint M12/98
نویسنده
چکیده
In this paper we derive rates of strong convergence for the kernel density estimator and for the Nadaraya-Watson estimator under the-mixing condition and under the condition of absolute regularity. A combination of an inequality of Bernstein type (Rio 1995) and an exponential inequality (cf. Fuk/Nagaev 1971) is the crucial tool for the proofs. Moreover, we consider the application of the main statements to the situation of autoregression.
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