Implementing semiparametric density estimation

Julian Faraway

doi:10.1016/0167-7152(90)90009-V

Implementing semiparametric density estimation

Julian Faraway

University of Michigan

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

Abstract

A semiparametric estimate of a density may be formed via the convex combination of a parametric and a nonparametric density estimate. It is shown that the some trimming is often necessary to obtain an appropriate proportion of these estimates.

Original language	English
Pages (from-to)	141-143
Number of pages	3
Journal	Statistics and Probability Letters
Volume	10
Issue number	2
DOIs	https://doi.org/10.1016/0167-7152(90)90009-V
Publication status	Published - 1 Jan 1990

Keywords

bandwidth selection
Nonparametric density estimation
trimming

ASJC Scopus subject areas

Statistics, Probability and Uncertainty
Statistics and Probability

Access to Document

10.1016/0167-7152(90)90009-V

Cite this

@article{9ee1d4bb95104fa2a3a4d03382618b94,

title = "Implementing semiparametric density estimation",

abstract = "A semiparametric estimate of a density may be formed via the convex combination of a parametric and a nonparametric density estimate. It is shown that the some trimming is often necessary to obtain an appropriate proportion of these estimates.",

keywords = "bandwidth selection, Nonparametric density estimation, trimming",

author = "Julian Faraway",

year = "1990",

month = jan,

day = "1",

doi = "10.1016/0167-7152(90)90009-V",

language = "English",

volume = "10",

pages = "141--143",

journal = "Statistics and Probability Letters",

issn = "0167-7152",

publisher = "Elsevier B.V.",

number = "2",

}

TY - JOUR

T1 - Implementing semiparametric density estimation

AU - Faraway, Julian

PY - 1990/1/1

Y1 - 1990/1/1

N2 - A semiparametric estimate of a density may be formed via the convex combination of a parametric and a nonparametric density estimate. It is shown that the some trimming is often necessary to obtain an appropriate proportion of these estimates.

AB - A semiparametric estimate of a density may be formed via the convex combination of a parametric and a nonparametric density estimate. It is shown that the some trimming is often necessary to obtain an appropriate proportion of these estimates.

KW - bandwidth selection

KW - Nonparametric density estimation

KW - trimming

UR - http://www.scopus.com/inward/record.url?scp=45149140785&partnerID=8YFLogxK

U2 - 10.1016/0167-7152(90)90009-V

DO - 10.1016/0167-7152(90)90009-V

M3 - Article

AN - SCOPUS:45149140785

SN - 0167-7152

VL - 10

SP - 141

EP - 143

JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

IS - 2

ER -

Implementing semiparametric density estimation

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this