In:
Stat, Wiley, Vol. 2, No. 1 ( 2013-12), p. 171-183
Kurzfassung:
In quantile smoothing, crossing of the estimated curves is a common nuisance, in particular with small data sets and dense sets of quantiles. Similar problems arise in expectile smoothing. We propose a novel method to avoid crossings. It is based on a location‐scale model for expectiles and estimates all expectile curves simultaneously in a bundle using iterative least asymmetrically weighted squares. In addition, we show how to estimate a density non‐parametrically from a set of expectiles. The model is applied to two data sets. Copyright © 2013 John Wiley & Sons Ltd
Materialart:
Online-Ressource
ISSN:
2049-1573
,
2049-1573
Sprache:
Englisch
Verlag:
Wiley
Publikationsdatum:
2013
ZDB Id:
2687133-6