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:: Volume 6, Issue 3 (Vol. 6, No. 3 2020) ::
Mathematical Researches 2020, 6(3): 0-0 Back to browse issues page
Comparison of the Gamma kernel and the orthogonal series methods of density estimation
Muhyiddin Izadi Dr. 1, Abdollah Jalilian Dr.2
1- Razi University , m.izadi@razi.ac.ir
2- Razi University
Abstract:   (415 Views)
The standard kernel density estimator suffers from a boundary bias issue
for probability density function of distributions on the positive real line. The Gamma
kernel estimators and orthogonal series estimators are two alternatives which are free of
boundary bias. In this paper, a simulation study is conducted to compare small-sample
performance of the Gamma kernel estimators and the orthogonal series density estimator with Laguerre and Hermite basis. We found that if the basis function is chosen based
on some partial knowledge about the shape of target density, then orthogonal series estimator can outperform the Gamma kernel estimator.
Keywords: Boundary bias, Mean integrated squared error, Smoothing parameter.
     
Type of Study: Original Manuscript | Subject: stat
Received: 2017/10/14 | Accepted: 2019/03/2 | Published: 2020/11/30 | ePublished: 2020/11/30
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Izadi M, Jalilian A. Comparison of the Gamma kernel and the orthogonal series methods of density estimation. Mathematical Researches. 2020; 6 (3)
URL: http://mmr.khu.ac.ir/article-1-2690-en.html


Volume 6, Issue 3 (Vol. 6, No. 3 2020) Back to browse issues page
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