On improve boundary effect in kernel distribution estimation

Tour, Madiha (2018) On improve boundary effect in kernel distribution estimation. Doctoral thesis, UNIVERSITE Mohamed Khider Biskra.

Thèse Doctorate, Madiha-30.02.2018.pdf

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In this thesis, we propose a new estimator for improve boundary effects in kernel estimator of the heavy-tailed distribution function specially the Pareto-type distributions and its bias, variance and mean squared error are determined. Kernel methods are widely used in many research areas in statistics. However, kernel estimators suffer from boundary effects when the support of the function to be estimated has finite end points. Boundary effects seriously affect the overall performance of the estimator. To remove the boundary effects, a variety of methods have been developed in the literature, the most widely used is the reflection, the transformation ... In this thesis, we introduce a new method of boundary correction when estimating the heavy-tailed distribution function. Our technique is kind of a generalized reflection method involving reflecting a transformation of the observed data by modified Champernowne distribution function

Item Type: Thesis (Doctoral)
Uncontrolled Keywords: Transformation; effet de bourd; Estimateur à noyau de la fonction de distribution; Eerreur quadratique moyenne; Erreur quadratique moyenne integre
Subjects: Q Science > QA Mathematics
Divisions: Faculté des Sciences Exactes et des Sciences de la Nature et de la Vie > Département de Mathématiques
Depositing User: BFSE
Date Deposited: 31 Jul 2018 08:58
Last Modified: 31 Jul 2018 08:58
URI: http://thesis.univ-biskra.dz/id/eprint/3835

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