Kernel Density Estimation With Binned Data

David W. Scott; Simon J. Sheather

doi:10.1080/03610928508828980

Kernel Density Estimation With Binned Data

David W. Scott
, Simon J. Sheather

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

92 Scopus citations

Abstract

Continuous data are often measured or used in binned or rounded form. In this paper we follow up on Hall's work analyzing the effect of using equally-spaced binned data in a kernel density estimator. It is shown that a surprisingly large amount of binning does not adversely affect the integrated mean squared error of a kernel estimate.

Original language	English
Pages (from-to)	1353-1359
Number of pages	7
Journal	Communications in Statistics - Theory and Methods
Volume	14
Issue number	6
DOIs	https://doi.org/10.1080/03610928508828980
State	Published - Jan 1 1985

Keywords

Nonpar ametric density estimation
rounded data

ASJC Scopus subject areas

Statistics and Probability

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10.1080/03610928508828980

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abstract = "Continuous data are often measured or used in binned or rounded form. In this paper we follow up on Hall's work analyzing the effect of using equally-spaced binned data in a kernel density estimator. It is shown that a surprisingly large amount of binning does not adversely affect the integrated mean squared error of a kernel estimate.",

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AU - Sheather, Simon J.

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AB - Continuous data are often measured or used in binned or rounded form. In this paper we follow up on Hall's work analyzing the effect of using equally-spaced binned data in a kernel density estimator. It is shown that a surprisingly large amount of binning does not adversely affect the integrated mean squared error of a kernel estimate.

KW - Nonpar ametric density estimation

KW - rounded data

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M3 - Article

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JO - Communications in Statistics - Theory and Methods

JF - Communications in Statistics - Theory and Methods

IS - 6

ER -

Kernel Density Estimation With Binned Data

Abstract

Keywords

ASJC Scopus subject areas

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