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Consistency of error density and distribution function estimators in nonparametric regression

โœ Scribed by Fuxia Cheng

Publisher
Elsevier Science
Year
2002
Tongue
English
Weight
140 KB
Volume
59
Category
Article
ISSN
0167-7152

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โœฆ Synopsis

This paper considers the problem of estimating the error density and distribution function in nonparametric regression models. Su cient conditions are given under which the histogram error density estimator based on nonparametric residuals is uniformly weakly and strongly consistent, and L 1 -consistent. The uniform consistency with a rate of the nonparametric residual empirical distribution function and the histogram error density estimator is also established.

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Consistent estimates of the mode of the
Consistent estimates of the mode of the probability density function in nonparametric deconvolution problems
โœ Mustapha Rachdi; Rachid Sabre ๐Ÿ“‚ Article ๐Ÿ“… 2000 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 111 KB

We propose two estimates of the mode of the probability density function for nonparametric deconvolution problems. In fact, we observe Y = X + , where is a measurement error with a known distribution f , and we are interesting by estimating the mode of fX the unknown probability density function of