Bayesian approach to the choice of smoothing parameter in kernel density estimation

2002 ◽  
Vol 14 (6) ◽  
pp. 655-664 ◽  
Author(s):  
Ashis Gangopadhyay ◽  
Kin Cheung
Keyword(s):  
Density Estimation ◽  
Bayesian Approach ◽  
Kernel Density Estimation ◽  
Kernel Density ◽  
Smoothing Parameter

scholarly journals One Value of Smoothing Parameter vs Interval of Smoothing Parameter Values in Kernel Density Estimation

2018 ◽  
Vol 6 (332) ◽  
pp. 73-86
Author(s):  
Aleksandra Katarzyna Baszczyńska
Keyword(s):  
Density Function ◽  
Density Estimation ◽  
Kernel Density Estimation ◽  
Ad Hoc ◽  
Kernel Density ◽  
Kernel Estimator ◽  
Smoothing Parameter ◽  
Smoothing Parameter Selection ◽  
Starting Point ◽  
Parameter Values

Ad hoc methods in the choice of smoothing parameter in kernel density estimation, al­though often used in practice due to their simplicity and hence the calculated efficiency, are char­acterized by quite big error. The value of the smoothing parameter chosen by Silverman method is close to optimal value only when the density function in population is the normal one. Therefore, this method is mainly used at the initial stage of determining a kernel estimator and can be used only as a starting point for further exploration of the smoothing parameter value. This paper pre­sents ad hoc methods for determining the smoothing parameter. Moreover, the interval of smooth­ing parameter values is proposed in the estimation of kernel density function. Basing on the results of simulation studies, the properties of smoothing parameter selection methods are discussed.

scholarly journals Author Correction: An extended Weight Kernel Density Estimation model forecasts COVID-19 onset risk and identifies spatiotemporal variations of lockdown effects in China

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Wenzhong Shi ◽  
Chengzhuo Tong ◽  
Anshu Zhang ◽  
Bin Wang ◽  
Zhicheng Shi ◽  
...  
Keyword(s):  
Density Estimation ◽  
Kernel Density Estimation ◽  
Kernel Density ◽  
Spatiotemporal Variations ◽  
Estimation Model

A Correction to this paper has been published: https://doi.org/10.1038/s42003-021-01924-6

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