Prediction via the Quantile-Copula Conditional Density Estimator

Olivier Faugeras

No 09-124, TSE Working Papers from Toulouse School of Economics (TSE)

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.

Keywords: nonparametric estimation; modal regressor; level-set (search for similar items in EconPapers)
Date: 2009-12
New Economics Papers: this item is included in nep-ecm
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Persistent link: https://EconPapers.repec.org/RePEc:tse:wpaper:22247

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