Statistical inference in nonlinear regression under heteroscedasticity

被引：0

作者：

Lim, Changwon ^{[1
]}

Sen, Pranab K. ^{[2
,3
]}

Peddada, Shyamal D. ^{[1
]}

机构：

[1] NIEHS, NIH, Biostat Branch, 111 TW Alexander Dr, Res Triangle Pk, NC 27709 USA

[2] Univ N Carolina, Dept Stat & Operat Res, Chapel Hill, NC 27599 USA

[3] Univ N Carolina, Dept Biostat, Chapel Hill, NC 27599 USA

来源：

SANKHYA-SERIES B-APPLIED AND INTERDISCIPLINARY STATISTICS | 2010年 / 72卷 / 02期

关键词：

Asymptotic normality; Dose-response study; Heteroscedasticity; Hill model; M-estimation procedure; Nonlinear regression model; Toxicology; Weighted M-estimator;

D O I：

暂无

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Nonlinear regression models are commonly used in toxicology and pharmacology. When fitting nonlinear models for such data, one needs to pay attention to error variance structure in the model and the presence of possible outliers or influential observations. In this paper, an M-estimation based procedure is considered in heteroscedastic nonlinear regression models where the standard deviation is modeled by a nonlinear function. The methodology is illustrated using toxicological data.

引用

页码：202 / 218

页数：17

共 50 条

[21] Heteroscedasticity checks for regression models [J].

Zhu, LX ;

Fujikoshi, Y ;

Naito, K .

SCIENCE IN CHINA SERIES A-MATHEMATICS PHYSICS ASTRONOMY, 2001, 44 (10) :1236-1252

[22] Statistical inference for a heteroscedastic regression model with φ-mixing errors [J].

Ding, Liwang ;

Chen, Ping ;

Yongming, Li .

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2022, 51 (08) :4658-4676

[23] A Modified Robust Estimator under Heteroscedasticity and Unusual Observations for Linear Regression Model [J].

Mubarik, Shagufta ;

Ilyas, Maryam .

ROMANIAN STATISTICAL REVIEW, 2021, (03) :23-36

[24] A new test of linear hypotheses in OLS regression under heteroscedasticity of unknown form [J].

Cai, Li ;

Hayes, Andrew F. .

JOURNAL OF EDUCATIONAL AND BEHAVIORAL STATISTICS, 2008, 33 (01) :21-40

[25] Statistical inference for panel data semiparametric partially linear regression models with heteroscedastic errors [J].

You, Jinhong ;

Zhou, Xian ;

Zhou, Yong .

JOURNAL OF MULTIVARIATE ANALYSIS, 2010, 101 (05) :1079-1101

[26] Designing to detect heteroscedasticity in a regression model [J].

Lanteri, Alessandro ;

Leorato, Samantha ;

Lopez-Fidalgo, Jesus ;

Tommasi, Chiara .

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2023, 85 (02) :315-326

[27] Profiling heteroscedasticity in linear regression models [J].

Zhou, Qian M. ;

Song, Peter X. -K. ;

Thompson, Mary E. .

CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 2015, 43 (03) :358-377

[28] Statistical inference in the partial functional linear expectile regression model [J].

Juxia Xiao ;

Ping Yu ;

Xinyuan Song ;

Zhongzhan Zhang .

Science China Mathematics, 2022, 65 :2601-2630

[29] Statistical inference in the partial functional linear expectile regression model [J].

Xiao, Juxia ;

Yu, Ping ;

Song, Xinyuan ;

Zhang, Zhongzhan .

SCIENCE CHINA-MATHEMATICS, 2022, 65 (12) :2601-2630

[30] TESTING OF CORRELATION AND HETEROSCEDASTICITY IN NONLINEAR REGRESSION MODELS WITH DBL(p,q,1) RANDOM ERRORS [J].

刘应安 ;

韦博成 .

ActaMathematicaScientia, 2008, (03) :613-632

← 1 2 3 4 5 →