Nonparametric estimation of extreme conditional quantiles

Nonparametric Estimation of Extreme Conditional Quantiles

The estimation of extreme conditional quantiles is an important issue in different scientific disciplines. Up to now, the extreme value literature focused mainly on estimation procedures based on i.i.d. samples. On the other hand, quantile regression based procedures work well for estimation within the data range i.e. the estimation of nonextreme quantiles but break down when main interest is i...

Functional nonparametric estimation of conditional extreme quantiles

− We address the estimation of quantiles from heavy-tailed distributions when functional covariate information is available and in the case where the order of the quantile converges to one as the sample size increases. Such ”extreme” quantiles can be located in the range of the data or near and even beyond the boundary of the sample, depending on the convergence rate of their order to one. Nonp...

Nonparametric estimation of the conditional tail index and extreme quantiles under random censoring

In this paper, we investigate the estimation of the tail index and extreme quantiles of a heavy-tailed distribution when some covariate information is available and the data are randomly right-censored. We construct several estimators by combining a moving-window technique (for tackling the covariate information) and the inverse probability-of-censoring weighting method, and we establish their ...

Nonparametric estimation of conditional quantiles using quantile regression trees

A nonparametric regression method that blends key features of piecewise polynomial quantile regression and tree-structured regression based on adaptive recursive partitioning of the covariate space is investigated. Unlike least squares regression trees, which concentrate on modeling the relationship between the response and the covariates at the center of the response distribution, our quantile...

Nonparametric Estimation of Conditional Quantiles Using Neural Networks