Abstract
Suppose that Y 1,Y 2,…Y n are independent and identically distributed n observations from convolution model Y=X+ɛ, where X is an unobserved random variable with unknown density, X f and ɛ is the measurement error with a known density function. Set \(\hat fn\left( x \right)\) to be a nonparametric kernel density estimator of f X , and the pointwise and uniform moderate deviations of statistic \(\sup _{x \in R} \left| {\hat f} \right._n \left( x \right) - \left| {\hat f} \right._n \left( { - x} \right)\) are given by Gine and Guillou’s exponential inequality.
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Biography: ZHAO Shoujiang, male, Lecturer, research direction: large deviations.
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Zhao, S., Liu, Q. Moderate deviations for a test of symmetry based on deconvolution kernel density estimators. Wuhan Univ. J. Nat. Sci. 16, 143–147 (2011). https://doi.org/10.1007/s11859-011-0727-x
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DOI: https://doi.org/10.1007/s11859-011-0727-x