Subset Selection in Linear Regression Using Generalized Ridge Estimator

Journal of Statistical Theory and Practice ◽

10.1080/15598608.2010.10411993 ◽

2010 ◽

Vol 4 (3) ◽

pp. 375-389

Author(s):

A. V. Dorugade ◽

D. N. Kashid

Keyword(s):

Linear Regression ◽

Subset Selection ◽

Ridge Estimator ◽

Generalized Ridge Estimator

Download Full-text

Generalized ridge estimator and model selection criteria in multivariate linear regression

Journal of Multivariate Analysis ◽

10.1016/j.jmva.2017.12.006 ◽

2018 ◽

Vol 165 ◽

pp. 243-261

Author(s):

Yuichi Mori ◽

Taiji Suzuki

Keyword(s):

Model Selection ◽

Linear Regression ◽

Selection Criteria ◽

Multivariate Linear Regression ◽

Ridge Estimator ◽

Model Selection Criteria ◽

Generalized Ridge Estimator

Download Full-text

Optimal generalized ridge estimator under the generalized cross-validation criterion in linear regression

Linear Algebra and its Applications ◽

10.1016/j.laa.2011.08.032 ◽

2012 ◽

Vol 436 (5) ◽

pp. 1238-1245 ◽

Author(s):

Xu-Qing Liu ◽

Hong-Yan Jiang

Keyword(s):

Linear Regression ◽

Cross Validation ◽

Ridge Estimator ◽

Generalized Cross Validation ◽

Validation Criterion ◽

Generalized Ridge Estimator

Download Full-text

Generalized ridge estimator in negative binomial regression model

Journal of Physics Conference Series ◽

10.1088/1742-6596/1897/1/012019 ◽

2021 ◽

Vol 1897 (1) ◽

pp. 012019

Author(s):

Nadwa Khazaal Rashad ◽

Nawal Mahmood Hammood ◽

Zakariya Yahya Algamal

Keyword(s):

Regression Model ◽

Negative Binomial ◽

Negative Binomial Regression ◽

Negative Binomial Regression Model ◽

Ridge Estimator ◽

Binomial Regression ◽

Generalized Ridge Estimator

Download Full-text

A MORE GENERAL CRITERION FOR SUBSET SELECTION IN MULTIPLE LINEAR REGRESSION

Communication in Statistics- Theory and Methods ◽

10.1081/sta-120003653 ◽

2002 ◽

Vol 31 (5) ◽

pp. 795-811 ◽

Author(s):

D. N. Kashid ◽

S. R. Kulkarni

Keyword(s):

Linear Regression ◽

Multiple Linear Regression ◽

Subset Selection ◽

General Criterion

Download Full-text

The Generalized Ridge Estimator of the Inverse Covariance Matrix

Journal of Computational and Graphical Statistics ◽

10.1080/10618600.2019.1604374 ◽

2019 ◽

Vol 28 (4) ◽

pp. 932-942 ◽

Author(s):

Wessel N. van Wieringen

Keyword(s):

Covariance Matrix ◽

Ridge Estimator ◽

Inverse Covariance Matrix ◽

Generalized Ridge Estimator

Download Full-text

On small sample properties of the almost unbiased generalized ridge estimator

Communication in Statistics- Theory and Methods ◽

10.1080/03610928608829203 ◽

1986 ◽

Vol 15 (5) ◽

pp. 1571-1578 ◽

Author(s):

Kazuhiro Ohtani

Keyword(s):

Small Sample ◽

Ridge Estimator ◽

Small Sample Properties ◽

Almost Unbiased ◽

Generalized Ridge Estimator

Download Full-text

lmSubsets: Exact Variable-Subset Selection in Linear Regression for R

Journal of Statistical Software ◽

10.18637/jss.v093.i03 ◽

2020 ◽

Vol 93 (3) ◽

Author(s):

Marc Hofmann ◽

Cristian Gatu ◽

Erricos J. Kontoghiorghes ◽

Ana Colubi ◽

Achim Zeileis

Keyword(s):

Linear Regression ◽

Subset Selection ◽

Variable Subset Selection ◽

Variable Subset

Download Full-text

A Local-branching Heuristic for the Best Subset Selection Problem in Linear Regression

2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) ◽

10.1109/ieem.2018.8607366 ◽

2018 ◽

Author(s):

Tamara Bigler ◽

Oliver Strub

Keyword(s):

Linear Regression ◽

Subset Selection ◽

Selection Problem ◽

Local Branching

Download Full-text

A mathematical programming approach for integrated multiple linear regression subset selection and validation

Pattern Recognition ◽

10.1016/j.patcog.2020.107565 ◽

2020 ◽

Vol 108 ◽

pp. 107565

Author(s):

Seokhyun Chung ◽

Young Woong Park ◽

Taesu Cheong

Keyword(s):

Linear Regression ◽

Mathematical Programming ◽

Multiple Linear Regression ◽

Subset Selection ◽

Programming Approach ◽

Mathematical Programming Approach

Download Full-text

Subset selection in multiple linear regression models: A hybrid of genetic and simulated annealing algorithms

Applied Mathematics and Computation ◽

10.1016/j.amc.2013.05.016 ◽

2013 ◽

Vol 219 (23) ◽

pp. 11018-11028 ◽

Author(s):

H. Hasan Örkcü

Keyword(s):

Simulated Annealing ◽

Linear Regression ◽

Multiple Linear Regression ◽

Regression Models ◽

Subset Selection ◽

Linear Regression Models ◽

Annealing Algorithms ◽

Multiple Linear Regression Models

Download Full-text