scholarly journals The Amount of Noise Inherent in Bandwidth Selection for a Kernel Density Estimator.

1985 ◽  
Author(s):  
P. Hall ◽  
J. S. Marron
Keyword(s):  
Bandwidth Selection ◽  
Kernel Density ◽  
Kernel Density Estimator ◽  
Density Estimator ◽  
Selection For

scholarly journals X-Entropy: A Parallelized Kernel Density Estimator with Automated Bandwidth Selection to Calculate Entropy

2021 ◽  
Vol 61 (4) ◽  
pp. 1533-1538
Author(s):  
Johannes Kraml ◽  
Florian Hofer ◽  
Patrick K. Quoika ◽  
Anna S. Kamenik ◽  
Klaus R. Liedl
Keyword(s):  
Bandwidth Selection ◽  
Kernel Density ◽  
Kernel Density Estimator ◽  
Density Estimator

scholarly journals Graphics processing units in acceleration of bandwidth selection for kernel density estimation

2013 ◽  
Vol 23 (4) ◽  
pp. 869-885 ◽  
Author(s):  
Witold Andrzejewski ◽  
Artur Gramacki ◽  
Jarosław Gramacki
Keyword(s):  
Graphics Processing Units ◽  
Bandwidth Selection ◽  
Kernel Density ◽  
Data Driven ◽  
Density Estimator ◽  
Algorithmic Optimization ◽  
Bandwidth Parameter ◽  
Selection For ◽  
Graphics Processing ◽  
Probability Density Function Pdf

Abstract The Probability Density Function (PDF) is a key concept in statistics. Constructing the most adequate PDF from the observed data is still an important and interesting scientific problem, especially for large datasets. PDFs are often estimated using nonparametric data-driven methods. One of the most popular nonparametric method is the Kernel Density Estimator (KDE). However, a very serious drawback of using KDEs is the large number of calculations required to compute them, especially to find the optimal bandwidth parameter. In this paper we investigate the possibility of utilizing Graphics Processing Units (GPUs) to accelerate the finding of the bandwidth. The contribution of this paper is threefold: (a) we propose algorithmic optimization to one of bandwidth finding algorithms, (b) we propose efficient GPU versions of three bandwidth finding algorithms and (c) we experimentally compare three of our GPU implementations with the ones which utilize only CPUs. Our experiments show orders of magnitude improvements over CPU implementations of classical algorithms.

Sign in / Sign up

Export Citation Format

Share Document