Kernel density estimation with adaptive varying window size

Vladimir Katkovnik; Ilya Shmulevich

doi:10.1016/S0167-8655(02)00127-7

Kernel density estimation with adaptive varying window size

Vladimir Katkovnik
, Ilya Shmulevich

Research output: Contribution to journal › Article › peer-review

66 Scopus citations

Abstract

A new method of kernel density estimation with a varying adaptive window size is proposed. It is based on the so called intersection of confidence intervals (ICI) rule. Several examples of the proposed method are given for different types of densities and the quality of the adaptive density estimate is assessed by means of numerical simulations.

Original language	English
Pages (from-to)	1641-1648
Number of pages	8
Journal	Pattern Recognition Letters
Volume	23
Issue number	14
DOIs	https://doi.org/10.1016/S0167-8655(02)00127-7
State	Published - Dec 2002
Externally published	Yes

Keywords

Density estimation
ICI rule
Kernel
Non-parametric
Parzen

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10.1016/S0167-8655(02)00127-7

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title = "Kernel density estimation with adaptive varying window size",

abstract = "A new method of kernel density estimation with a varying adaptive window size is proposed. It is based on the so called intersection of confidence intervals (ICI) rule. Several examples of the proposed method are given for different types of densities and the quality of the adaptive density estimate is assessed by means of numerical simulations.",

keywords = "Density estimation, ICI rule, Kernel, Non-parametric, Parzen",

author = "Vladimir Katkovnik and Ilya Shmulevich",

year = "2002",

month = dec,

doi = "10.1016/S0167-8655(02)00127-7",

language = "English",

volume = "23",

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T1 - Kernel density estimation with adaptive varying window size

AU - Katkovnik, Vladimir

AU - Shmulevich, Ilya

PY - 2002/12

Y1 - 2002/12

N2 - A new method of kernel density estimation with a varying adaptive window size is proposed. It is based on the so called intersection of confidence intervals (ICI) rule. Several examples of the proposed method are given for different types of densities and the quality of the adaptive density estimate is assessed by means of numerical simulations.

AB - A new method of kernel density estimation with a varying adaptive window size is proposed. It is based on the so called intersection of confidence intervals (ICI) rule. Several examples of the proposed method are given for different types of densities and the quality of the adaptive density estimate is assessed by means of numerical simulations.

KW - Density estimation

KW - ICI rule

KW - Kernel

KW - Non-parametric

KW - Parzen

UR - https://www.scopus.com/pages/publications/0036885193

U2 - 10.1016/S0167-8655(02)00127-7

DO - 10.1016/S0167-8655(02)00127-7

M3 - Article

AN - SCOPUS:0036885193

SN - 0167-8655

VL - 23

SP - 1641

EP - 1648

JO - Pattern Recognition Letters

JF - Pattern Recognition Letters

IS - 14

ER -

Kernel density estimation with adaptive varying window size

Abstract

Keywords

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