A SYNTHESIS OF STEIN-RULE AND MIXED REGRESSION PROCEDURES IN LINEAR-REGRESSION MODELS UNDER NON-NORMALITY

被引：3

作者：

TRACY, DS ^{[1
]}

SRIVASTAVA, AK ^{[1
]}

机构：

[1] UNIV LUCKNOW,DEPT STAT,LUCKNOW 226007,UTTAR PRADESH,INDIA

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 1988年 / 17卷 / 03期

关键词：

D O I：

10.1080/03610928808829649

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：

引用

页码：691 / 704

页数：14

共 47 条

[31] Alternative procedures to discriminate non nested multivariate linear regression models
Araújo, MI
Fernandes, M
Pereira, BD
[J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2005, 34 (9-10) : 2047 - 2062
[32] Asymptotic normality in multivariate nonlinear regression and multivariate generalized linear regression models under repeated measurements with missing data
Garren, ST
Peddada, SD
[J]. STATISTICS & PROBABILITY LETTERS, 2000, 48 (03) : 293 - 302
[33] THE MINIMUM ERROR VARIANCE RULE FOR NON-LINEAR REGRESSION-MODELS
MCALEER, M
[J]. ECONOMICS LETTERS, 1980, 6 (01) : 17 - 21
[34] On the Stein-Type Liu Estimator and Positive-Rule Stein-Type Liu Estimator in Multiple Linear Regression Models
Xu, Jianwen
Yang, Hu
[J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2012, 41 (05) : 791 - 808
[35] A Comparison of Logistic Regression Models for Dif Detection in Polytomous Items: The Effect of Small Sample Sizes and Non-Normality of Ability Distributions
Kaya, Yasemin
Leite, Walter L.
Miller, M. David
[J]. INTERNATIONAL JOURNAL OF ASSESSMENT TOOLS IN EDUCATION, 2015, 2 (01): : 22 - 39
[36] ASYMPTOTIC APPROXIMATIONS TO THE GAIN OF THE 2SHI OVER STEIN-ESTIMATORS IN LINEAR-REGRESSION MODELS WHEN THE DISTURBANCES ARE SMALL
VANHOA, T
CHATURVEDI, A
[J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 1993, 22 (10) : 2777 - 2782
[37] Second-order bias-corrected AIC in multivariate normal linear models under non-normality
Yanagihara, Hirokazu
Kamo, Ken-Ichi
Tonda, Tetsuji
[J]. CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 2011, 39 (01): : 126 - 146
[38] A SAS® CODE TO CORRECT FOR NON-NORMALITY AND NON-CONSTANT VARIANCE IN REGRESSION AND ANOVA MODELS USING THE BOX–COX METHOD OF POWER TRANSFORMATION
ZIAD A. MALAEB
[J]. Environmental Monitoring and Assessment, 1997, 47 : 255 - 273
[39] Non-linear and mixed regression models in predicting sustainable concrete strength
Jin, Ruoyu
Chen, Qian
Soboyejo, Alfred B. O.
[J]. CONSTRUCTION AND BUILDING MATERIALS, 2018, 170 : 142 - 152
[40] NESTED AND NON-NESTED PROCEDURES FOR TESTING LINEAR AND LOG-LINEAR REGRESSION-MODELS
BERA, AK
MCALEER, M
[J]. SANKHYA-THE INDIAN JOURNAL OF STATISTICS SERIES B, 1989, 51 : 212 - 224

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