Relative Deficiency of Kernel Type Estimators of Quantiles

Functional kernel estimators of large conditional quantiles

Functional kernel estimators of conditional extreme quantiles

We address the estimation of “extreme” conditional quantiles i.e. when their order converges to one as the sample size increases. Conditions on the rate of convergence of their order to one are provided to obtain asymptotically Gaussian distributed kernel estimators. A Weissman-type estimator and kernel estimators of the conditional tailindex are derived, permitting to estimate extreme conditio...

On M-estimators of Approximate Quantiles and Approximate Conditional Quantiles

M-estimators introduced in Huber (1964) provide a class of robust estimators of a center of symmetry of a symmetric probability distribution which also have very high eeciency at the model. However it is not clear what they do estimate when the probability distributions are nonsymmetric. In this paper we rst show that in the case of arbitrary, not necessarily symmetric probabilty distributions,...

the investigation of the relationship between type a and type b personalities and quality of translation

چکیده ندارد.

Nonparametric Prewhitening Estimators for Conditional Quantiles

We define a nonparametric prewhitening method for estimating conditional quantiles based on local linear quantile regression. We characterize the bias, variance and asymptotic normality of the proposed estimator. Under weak conditions our estimator can achieve bias reduction and have the same variance as the local linear quantile estimators. A small set of Monte Carlo simulations is carried out...