Kernel adjusted density estimation

We propose and study a kernel estimator of a density in which the kernel is adapted to the data but not fixed. The smoothing procedure is followed by a location-scale transformation to reduce bias and variance. The new method naturally leads to an adaptive choice of the smoothing parameters which avoids asymptotic expansions.

MoreLess

Year of publication:	2011
Authors:	Srihera, Ramidha ; Stute, Winfried
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 81.2011, 5, p. 571-579
Publisher:	Elsevier
Subject:	Kernel density estimator Adaptive choice

Online Resource

Check full text access |

More access options

Check Google Scholar

In libraries world-wide (WorldCat)

In German libraries (KVK)

subito order

I need help

More details

Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008868836