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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/16745

Title: Preadjusted non-parametric estimation of a conditional distribution function
Authors: VERAVERBEKE, Noel
Gijbels, Irène
OMELKA, Marek
Issue Date: 2014
Citation: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 76 (2), p. 399-438
Abstract: The paper deals with non-parametric estimation of a conditional distribution function. We suggest a method of preadjusting the original observations non-parametrically through location and scale, to reduce the bias of the estimator.We derive the asymptotic properties of the estimator proposed. A simulation study investigating the finite sample performances of the estimators discussed is provided and reveals the gain that can be achieved. It is also shown how the idea of the preadjusting opens the path to improved estimators in other settings such as conditional quantile and density estimation, and conditional survival function estimation in the case of censored data.
URI: http://hdl.handle.net/1942/16745
ISI #: 000331369500004
ISSN: 1369-7412
Category: A1
Type: Journal Contribution
Validation: ecoom, 2015
Appears in Collections: Research publications

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