LAD-Lasso variable selection for doubly censored median regression models

Communication in Statistics- Theory and Methods ◽

10.1080/03610926.2014.904357 ◽

2016 ◽

Vol 45 (12) ◽

pp. 3658-3667 ◽

Author(s):

Xiuqing Zhou ◽

Guoxiang Liu

Keyword(s):

Variable Selection ◽

Regression Models ◽

Median Regression ◽

Doubly Censored ◽

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Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases

BMC Bioinformatics ◽

10.1186/1471-2105-9-251 ◽

2008 ◽

Vol 9 (1) ◽

Author(s):

Min Zhang ◽

Dabao Zhang ◽

Martin T Wells

Keyword(s):

Variable Selection ◽

Incomplete Data ◽

Regression Models ◽

Data Mapping ◽

Mapping Qtl ◽

Large P Small N ◽

Selection For ◽

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Methods of Statistical Inference for Median Regression Models with Doubly Censored Data

Communication in Statistics- Theory and Methods ◽

10.1080/03610920903200009 ◽

2010 ◽

Vol 39 (17) ◽

pp. 3140-3152 ◽

Author(s):

Xiuqing Zhou ◽

Ningzhong Shi

Keyword(s):

Statistical Inference ◽

Censored Data ◽

Regression Models ◽

Median Regression ◽

Doubly Censored Data ◽

Doubly Censored

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Modified See Variable Selection For Linear Instrumental Variable Regression Models

Communication in Statistics- Theory and Methods ◽

10.1080/03610926.2013.777739 ◽

2014 ◽

pp. 00-00

Author(s):

Peixin Zhao ◽

Liugen Xue

Keyword(s):

Variable Selection ◽

Instrumental Variable ◽

Regression Models ◽

Instrumental Variable Regression ◽

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Dirichlet-Multinomial Regression Models with Bayesian Variable Selection for Microbiome Data

10.1007/978-3-030-73351-3_10 ◽

2021 ◽

pp. 249-270

Author(s):

Matthew D. Koslovsky ◽

Marina Vannucci

Keyword(s):

Variable Selection ◽

Regression Models ◽

Bayesian Variable Selection ◽

Multinomial Regression ◽

Selection For ◽

Microbiome Data

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Bayesian Variable Selection for Gaussian Copula Regression Models

Journal of Computational and Graphical Statistics ◽

10.1080/10618600.2020.1840997 ◽

2020 ◽

pp. 1-16

Author(s):

Angelos Alexopoulos ◽

Leonardo Bottolo

Keyword(s):

Variable Selection ◽

Regression Models ◽

Bayesian Variable Selection ◽

Gaussian Copula ◽

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Consistent variable selection for functional regression models

Journal of Multivariate Analysis ◽

10.1016/j.jmva.2015.06.007 ◽

2016 ◽

Vol 146 ◽

pp. 63-71 ◽

Author(s):

Julian A.A. Collazos ◽

Ronaldo Dias ◽

Adriano Z. Zambom

Keyword(s):

Variable Selection ◽

Regression Models ◽

Functional Regression ◽

Selection For ◽

Functional Regression Models

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Simultaneous variable selection for heteroscedastic regression models

Science China Mathematics ◽

10.1007/s11425-010-4147-8 ◽

2011 ◽

Vol 54 (3) ◽

pp. 515-530 ◽

Author(s):

ZhongZhan Zhang ◽

DaRong Wang

Keyword(s):

Variable Selection ◽

Regression Models ◽

Heteroscedastic Regression ◽

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Penalized Empirical Likelihood based Variable Selection for Partially Linear Quantile Regression Models with Missing Responses

Hacettepe Journal of Mathematics and Statistics ◽

10.15672/hjms.201614120416 ◽

2016 ◽

Vol 47 (141) ◽

pp. 1-1

Author(s):

Xinrong Tang ◽

Peixin Zhao

Keyword(s):

Variable Selection ◽

Quantile Regression ◽

Empirical Likelihood ◽

Regression Models ◽

Missing Responses ◽

Partially Linear ◽

Selection For ◽

Penalized Empirical Likelihood

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Robust variable selection for finite mixture regression models

Annals of the Institute of Statistical Mathematics ◽

10.1007/s10463-017-0602-4 ◽

2017 ◽

Vol 70 (3) ◽

pp. 489-521 ◽

Author(s):

Qingguo Tang ◽

R. J. Karunamuni

Keyword(s):

Variable Selection ◽

Regression Models ◽

Finite Mixture ◽

Mixture Regression ◽

Finite Mixture Regression ◽

Selection For ◽

Mixture Regression Models

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Bayesian Variable Selection for the Seemingly Unrelated Regression Models with a Large Number of Predictors

JOURNAL OF THE JAPAN STATISTICAL SOCIETY ◽

10.14490/jjss.41.187 ◽

2012 ◽

Vol 41 (2) ◽

pp. 187-203 ◽

Author(s):

Tomohiro Ando

Keyword(s):

Variable Selection ◽

Regression Models ◽

Bayesian Variable Selection ◽

Seemingly Unrelated Regression ◽

Unrelated Regression ◽

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