Asymptotic properties of covariate-adjusted regression with correlated errors

Damla Şentürk, Danh V. Nguyen

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

In covariate-adjusted regression (CAR), the response (Y) and predictors (Xr, r = 1, ..., p) are not observed directly. Estimation is based on n independent observations {over(Yi, ̃), over(X, ̃)r i, Ui}i = 1 n, where over(Y, ̃)i = ψ (Ui) Yi, over(X, ̃)r i = φ{symbol}r (Ui) Xr i and ψ ({dot operator}) and {φ{symbol}r ({dot operator})}r = 1 p are unknown functions. In this paper, we discuss the asymptotic properties of this method when the observations are correlated, as in regression models for repeated measurements.

Original languageEnglish (US)
Pages (from-to)1175-1180
Number of pages6
JournalStatistics and Probability Letters
Volume79
Issue number9
DOIs
StatePublished - May 1 2009

Fingerprint

Correlated Errors
Asymptotic Properties
Covariates
Regression
Repeated Measurements
Predictors
Regression Model
Unknown
Operator
Observation
Asymptotic properties
Symbol
Regression model

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Statistics and Probability

Cite this

Asymptotic properties of covariate-adjusted regression with correlated errors. / Şentürk, Damla; Nguyen, Danh V.

In: Statistics and Probability Letters, Vol. 79, No. 9, 01.05.2009, p. 1175-1180.

Research output: Contribution to journalArticle

Şentürk, Damla ; Nguyen, Danh V. / Asymptotic properties of covariate-adjusted regression with correlated errors. In: Statistics and Probability Letters. 2009 ; Vol. 79, No. 9. pp. 1175-1180.
@article{2a57049fe35249b1bd5126923b442369,
title = "Asymptotic properties of covariate-adjusted regression with correlated errors",
abstract = "In covariate-adjusted regression (CAR), the response (Y) and predictors (Xr, r = 1, ..., p) are not observed directly. Estimation is based on n independent observations {over(Yi, ̃), over(X, ̃)r i, Ui}i = 1 n, where over(Y, ̃)i = ψ (Ui) Yi, over(X, ̃)r i = φ{symbol}r (Ui) Xr i and ψ ({dot operator}) and {φ{symbol}r ({dot operator})}r = 1 p are unknown functions. In this paper, we discuss the asymptotic properties of this method when the observations are correlated, as in regression models for repeated measurements.",
author = "Damla Şent{\"u}rk and Nguyen, {Danh V.}",
year = "2009",
month = "5",
day = "1",
doi = "10.1016/j.spl.2008.12.024",
language = "English (US)",
volume = "79",
pages = "1175--1180",
journal = "Statistics and Probability Letters",
issn = "0167-7152",
publisher = "Elsevier",
number = "9",

}

TY - JOUR

T1 - Asymptotic properties of covariate-adjusted regression with correlated errors

AU - Şentürk, Damla

AU - Nguyen, Danh V.

PY - 2009/5/1

Y1 - 2009/5/1

N2 - In covariate-adjusted regression (CAR), the response (Y) and predictors (Xr, r = 1, ..., p) are not observed directly. Estimation is based on n independent observations {over(Yi, ̃), over(X, ̃)r i, Ui}i = 1 n, where over(Y, ̃)i = ψ (Ui) Yi, over(X, ̃)r i = φ{symbol}r (Ui) Xr i and ψ ({dot operator}) and {φ{symbol}r ({dot operator})}r = 1 p are unknown functions. In this paper, we discuss the asymptotic properties of this method when the observations are correlated, as in regression models for repeated measurements.

AB - In covariate-adjusted regression (CAR), the response (Y) and predictors (Xr, r = 1, ..., p) are not observed directly. Estimation is based on n independent observations {over(Yi, ̃), over(X, ̃)r i, Ui}i = 1 n, where over(Y, ̃)i = ψ (Ui) Yi, over(X, ̃)r i = φ{symbol}r (Ui) Xr i and ψ ({dot operator}) and {φ{symbol}r ({dot operator})}r = 1 p are unknown functions. In this paper, we discuss the asymptotic properties of this method when the observations are correlated, as in regression models for repeated measurements.

UR - http://www.scopus.com/inward/record.url?scp=63549105565&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=63549105565&partnerID=8YFLogxK

U2 - 10.1016/j.spl.2008.12.024

DO - 10.1016/j.spl.2008.12.024

M3 - Article

AN - SCOPUS:63549105565

VL - 79

SP - 1175

EP - 1180

JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

SN - 0167-7152

IS - 9

ER -