Conditional Quantile for Truncated Dependent data

YAHIA, DJABRANE (2010) Conditional Quantile for Truncated Dependent data. ["eprint_fieldopt_thesis_type_phd" not defined] thesis, Université Mohamed Khider Biskra.

[img]
Preview
Text
math_d2_2010.pdf

Download (1MB) | Preview

Abstract

In this thesis we study some asymptotic properties of the kernel conditional quantile estimator when the interest variable is subject to random left truncation. The uniform strong convergence rate of the estimator is obtained. In addition, it is shown that, under regularity conditions and suitably normalized, the kernel estimate of the conditional quantile is asymptotically normally distributed. Our interest in conditional quantile estimation is motivated by it's robusteness, the constructing of the confidence bands and the forecasting from time series data. Our results are obtained in a more general setting (strong mixing) which includes time series modelling as a special case .

Item Type: Thesis (["eprint_fieldopt_thesis_type_phd" not defined])
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: Admin01 TMLBiskra
Date Deposited: 10 Dec 2014 11:11
Last Modified: 10 Dec 2014 11:11
URI: http://thesis.univ-biskra.dz/id/eprint/1046

Actions (login required)

View Item View Item