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http://hdl.handle.net/20.500.12358/21427
TitleKernel Nearest Neighbor Estimator for the Regression Quantile
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Abstract

In this thesis, we study the kernel estimation of the conditional probability density function and two of its aspects, the conditional mode and the conditional quantiles. For the conditional mode, we study the asymptotic normality of its kernel estimation from [30] and the conditions under which the conditional mode estimated at finite distinct points is asymptotically normally distributed. Also, we study the kernel estimation for the conditional quantile from [1] and we study the conditions under which the joint distribution of several conditional quantile is asymptotically normally distributed.

Authors
Abu Shamala, Ibrahim Ahmed
Supervisors
Salha, Raid B.
Typeرسالة ماجستير
Date2014
LanguageEnglish
Publisherالجامعة الإسلامية - غزة
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  • PhD and MSc Theses- Faculty of Science [445]
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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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