An Additive Sparse Penalty for Variable Selection in High-Dimensional Linear Regression Model

Sangin Lee

doi:10.5351/csam.2015.22.2.147

An Additive Sparse Penalty for Variable Selection in High-Dimensional Linear Regression Model

Communications for Statistical Applications and Methods ◽

10.5351/csam.2015.22.2.147 ◽

2015 ◽

Vol 22 (2) ◽

pp. 147-157 ◽

Cited By ~ 2

Author(s):

Sangin Lee

Keyword(s):

Linear Regression ◽

Variable Selection ◽

Regression Model ◽

Linear Regression Model ◽

High Dimensional

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High-dimensional QSAR modelling using penalized linear regression model with L1/2-norm

SAR and QSAR in Environmental Research ◽

10.1080/1062936x.2016.1228696 ◽

2016 ◽

Vol 27 (9) ◽

pp. 703-719 ◽

Cited By ~ 8

Author(s):

Z. Y. Algamal ◽

M. H. Lee ◽

A. M. Al-Fakih ◽

M. Aziz

Keyword(s):

Linear Regression ◽

Regression Model ◽

Linear Regression Model ◽

High Dimensional ◽

Qsar Modelling

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MLRMPA: An R package of multiple linear regression model population analysis based on a cluster sampling technique for variable selection of high dimensional data

Chemometrics and Intelligent Laboratory Systems ◽

10.1016/j.chemolab.2014.01.010 ◽

2014 ◽

Vol 132 ◽

pp. 124-132 ◽

Cited By ~ 4

Author(s):

Meihong Xie ◽

Fangfang Deng ◽

Xiaoyun Zhang ◽

Yueli Tian ◽

Peizhen Li ◽

...

Keyword(s):

Linear Regression ◽

Regression Model ◽

Linear Regression Model ◽

Population Analysis ◽

Multiple Linear Regression Model ◽

Sampling Technique ◽

R Package ◽

High Dimensional ◽

Cluster Sampling ◽

Selection Of

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Bayesian variable selection and coefficient estimation in heteroscedastic linear regression model

Journal of Applied Statistics ◽

10.1080/02664763.2018.1432576 ◽

2018 ◽

Vol 45 (14) ◽

pp. 2643-2657 ◽

Cited By ~ 2

Author(s):

Taha Alshaybawee ◽

Rahim Alhamzawi ◽

Habshah Midi ◽

Intisar Ibrahim Allyas

Keyword(s):

Linear Regression ◽

Variable Selection ◽

Regression Model ◽

Linear Regression Model ◽

Bayesian Variable Selection ◽

Coefficient Estimation

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A nonlinear mixed–integer programming approach for variable selection in linear regression model

Communications in Statistics - Simulation and Computation ◽

10.1080/03610918.2021.1990323 ◽

2021 ◽

pp. 1-12

Author(s):

Mahdi Roozbeh ◽

Saman Babaie–Kafaki ◽

Zohre Aminifard

Keyword(s):

Integer Programming ◽

Linear Regression ◽

Variable Selection ◽

Regression Model ◽

Mixed Integer Programming ◽

Linear Regression Model ◽

Mixed Integer ◽

Programming Approach

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The likelihood ratio test for high-dimensional linear regression model

Communication in Statistics- Theory and Methods ◽

10.1080/03610926.2016.1183785 ◽

2017 ◽

Vol 46 (17) ◽

pp. 8479-8492 ◽

Cited By ~ 1

Author(s):

Junshan Xie ◽

Nannan Xiao

Keyword(s):

Linear Regression ◽

Regression Model ◽

Likelihood Ratio ◽

Likelihood Ratio Test ◽

Linear Regression Model ◽

High Dimensional ◽

Ratio Test

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Variable selection in partly linear regression model with diverging dimensions for right censored data

Statistica Sinica ◽

10.5705/ss.2010.267 ◽

2012 ◽

Vol 22 (3) ◽

Cited By ~ 12

Author(s):

Shuangge Ma ◽

Pang Du

Keyword(s):

Linear Regression ◽

Variable Selection ◽

Regression Model ◽

Censored Data ◽

Linear Regression Model ◽

Right Censored Data

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A monte carlo study of variable selection and inferences in a two stage random coefficient linear regression model with unbalanced data

Communication in Statistics- Theory and Methods ◽

10.1080/03610929108830740 ◽

1991 ◽

Vol 20 (12) ◽

pp. 3761-3791 ◽

Cited By ~ 9

Author(s):

So Young Sohn ◽

Mainak Mazumdar

Keyword(s):

Monte Carlo ◽

Linear Regression ◽

Variable Selection ◽

Regression Model ◽

Linear Regression Model ◽

Monte Carlo Study ◽

Random Coefficient ◽

Unbalanced Data ◽

Two Stage

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Using Nonnegative Minimum Biased Quadratic Estimation for Variable Selection in the Linear Regression Model

Proceedings of the International Conference on Linear Statistical Inference LINSTAT ’93 ◽

10.1007/978-94-011-1004-4_7 ◽

1994 ◽

pp. 65-71 ◽

Cited By ~ 1

Author(s):

Stanislaw Gnot ◽

Henning Knautz ◽

Götz Trenkler

Keyword(s):

Linear Regression ◽

Variable Selection ◽

Regression Model ◽

Linear Regression Model ◽

Quadratic Estimation

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Reduced rank regression with matrix projections for high-dimensional multivariate linear regression model

Electronic Journal of Statistics ◽

10.1214/21-ejs1895 ◽

2021 ◽

Vol 15 (2) ◽

Author(s):

Wenxing Guo ◽

Narayanaswamy Balakrishnan ◽

Mengjie Bian

Keyword(s):

Linear Regression ◽

Regression Model ◽

Linear Regression Model ◽

Multivariate Linear Regression ◽

High Dimensional ◽

Multivariate Linear Regression Model ◽

Reduced Rank Regression ◽

Rank Regression ◽

Reduced Rank

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Tuning Parameter Selection Based on Blocked $$3\times 2$$ Cross-Validation for High-Dimensional Linear Regression Model

Neural Processing Letters ◽

10.1007/s11063-019-10105-w ◽

2019 ◽

Vol 51 (1) ◽

pp. 1007-1029

Author(s):

Xingli Yang ◽

Yu Wang ◽

Ruibo Wang ◽

Mengmeng Chen ◽

Jihong Li

Keyword(s):

Linear Regression ◽

Regression Model ◽

Linear Regression Model ◽

Cross Validation ◽

Parameter Selection ◽

Tuning Parameter ◽

High Dimensional

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