Understanding nonparametric estimation for clustered data

Richard Huggins

doi:10.1093/biomet/93.2.486

Understanding nonparametric estimation for clustered data

Richard Huggins^*

^*Corresponding author for this work

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

4 Citations (Scopus)

Abstract

In this note we give an alternative formulation of the nonparametric estimators of Wang (2003) with the identity link. This results in a closed form of the estimator that has computational advantages and gives insight into the rationale behind the estimator.

Original language	English
Pages (from-to)	486-489
Number of pages	4
Journal	Biometrika
Volume	93
Issue number	2
DOIs	https://doi.org/10.1093/biomet/93.2.486
Publication status	Published - Jun 2006

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title = "Understanding nonparametric estimation for clustered data",

abstract = "In this note we give an alternative formulation of the nonparametric estimators of Wang (2003) with the identity link. This results in a closed form of the estimator that has computational advantages and gives insight into the rationale behind the estimator.",

keywords = "Clustered data, Nonparametric estimation",

author = "Richard Huggins",

year = "2006",

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language = "English",

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pages = "486--489",

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AB - In this note we give an alternative formulation of the nonparametric estimators of Wang (2003) with the identity link. This results in a closed form of the estimator that has computational advantages and gives insight into the rationale behind the estimator.

KW - Clustered data

KW - Nonparametric estimation

UR - https://www.scopus.com/pages/publications/33745625826

U2 - 10.1093/biomet/93.2.486

DO - 10.1093/biomet/93.2.486

M3 - Article

SN - 0006-3444

VL - 93

SP - 486

EP - 489

JO - Biometrika

JF - Biometrika

IS - 2

ER -

Understanding nonparametric estimation for clustered data

Abstract

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