Prediction via the Quantile-Copula Conditional Density Estimator

Faugeras, Olivier (2009) Prediction via the Quantile-Copula Conditional Density Estimator. TSE Working Paper, n. 09-124, Toulouse

WarningThere is a more recent version of this item available.
[img]
Preview
Text
Download (513kB) | Preview
Official URL: http://tse-fr.eu/pub/22247

Abstract

To make a prediction of a response variable from an explanatory one which takes into account features such as multimodality, a nonparametric approach based on an estimate of the conditional
density is advocated and considered. In particular, we build point and interval predictors based on the quantile-copula estimator of the conditional density by Faugeras [8]. The consistency of these
predictors is proved through a uniform consistency result of the conditional density estimator. Eventually, the practical implementation of these predictors is discussed. A simulation on a real data set illustrates the proposed methods.

Item Type: Monograph (Working Paper)
Language: English
Date: 7 December 2009
Place of Publication: Toulouse
Uncontrolled Keywords: nonparametric estimation, modal regressor, level-set
Subjects: B- ECONOMIE ET FINANCE
Divisions: TSE-R (Toulouse)
Institution: Université Toulouse 1 Capitole
Site: UT1
Date Deposited: 18 Jan 2012 06:01
Last Modified: 19 Mar 2018 15:19
["eprint_fieldname_oai_identifier" not defined]: oai:tse-fr.eu:22247
URI: http://publications.ut-capitole.fr/id/eprint/3275

Available Versions of this Item

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year