Kernel density estimation and its application
Authors:
- Stanisław Węglarczyk
Abstract
Kernel density estimation is a technique for estimation of probability density function that is a must-have enabling the user to better analyse the studied probability distribution than when using a traditional histogram. Unlike the histogram, the kernel technique produces smooth estimate of the pdf, uses all sample points' locations and more convincingly suggest multimodality. In its two-dimensional applications, kernel estimation is even better as the 2D histogram requires additionally to define the orientation of 2D bins. Two concepts play fundamental role in kernel estimation: kernel function shape and coefficient of smoothness, of which the latter is crucial to the method. Several real-life examples, both for univariate and bivariate applications, are shown.
- Record ID
- CUTd32f0a5fe20c427e8fb04eabddebe231
- Publication categories
- ; ;
- Author
- Journal series
- ITM Web of Conferences , ISSN , e-ISSN 2271-2097, Irregular
- Issue year
- 2018
- Vol
- 23
- Pages
- [1-8]
- Article number
- 00037
- Other elements of collation
- rys.; tab.; wykr.; Bibliografia (na s.) - 7-8; Bibliografia (liczba pozycji) - 43; Oznaczenie streszczenia - Abstr.; Numeracja w czasopiśmie - Vol. 23
- Conference
- XLVIII Seminar of Applied Mathematics, 2018, 09-09-2018 - 11-09-2018, Boguszów-Gorce, Polska
- Keywords in English
- kernel density estimation, annual maximum discharge, annual minimum discharge, annual maximum daily precipitation
- DOI
- DOI:10.1051/itmconf/20182300037 Opening in a new tab
- URL
- https://www.itm-conferences.org/articles/itmconf/abs/2018/08/itmconf_sam2018_00037/itmconf_sam2018_00037.html Opening in a new tab
- Language
- eng (en) English
- License
- Score (nominal)
- 15
- Additional fields
- Indeksowana w: Web of Science
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUTd32f0a5fe20c427e8fb04eabddebe231/
- URN
urn:pkr-prod:CUTd32f0a5fe20c427e8fb04eabddebe231
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.