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Prediction via the Quantile-Copula Conditional Density Estimator

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  • Faugeras, Olivier

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.

Suggested Citation

  • Faugeras, Olivier, 2009. "Prediction via the Quantile-Copula Conditional Density Estimator," TSE Working Papers 09-124, Toulouse School of Economics (TSE).
  • Handle: RePEc:tse:wpaper:22247
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    References listed on IDEAS

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    1. Faugeras, Olivier P., 2009. "A quantile-copula approach to conditional density estimation," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 2083-2099, October.
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    More about this item

    Keywords

    nonparametric estimation; modal regressor; level-set;
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