Some Large Deviations Limit Theorems in Conditional Nonparametric Statistics
Author:
Djamal Louani a
| Affiliation: | a L.S.T.A, Paris 6 University, France |
DOI:
10.1080/02331889908802690
Publication Frequency:
6 issues per year
Subjects:
Mathematical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
Formats available:
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Abstract
We establish pointwise and uniform large deviations limit theorems of Chernoff-type for the conditional empirical process. On the other hand, we state the pointwise large deviations theorem for the Nadaraya-Watson estimator of the regression function. The estimations are based on sequences of independent and identically distributed random vectors. We derive then some implications of our results in the study of asymptotic efficiency of goodness-of-fit test based on uniform deviation of the conditional empirical distribution function with respect to its theoretical distribution. Moreover, we deduce the inaccuracy rate in conditional distribution functions estimation.
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| Keywords: Large deviations; nonparametric estimation; conditional empirical process; regression function; Bahadur exact slope; inaccuracy rate |
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