Improved empirical likelihood inference and variable selection for generalized linear models with longitudinal nonignorable dropouts

Linear Models ◽

Likelihood Inference ◽

Bayesian variable selection for high dimensional generalized linear models: Convergence rates of the fitted densities

The Annals of Statistics ◽

10.1214/009053607000000019 ◽

2007 ◽

Vol 35 (4) ◽

pp. 1487-1511 ◽

Cited By ~ 34

Author(s):

Wenxin Jiang

Keyword(s):

Variable Selection ◽

Linear Models ◽

Convergence Rates ◽

Bayesian Variable Selection ◽

High Dimensional ◽

Instrumental variable based variable selection for generalized linear models with endogenous covariates

Communications in Statistics - Simulation and Computation ◽

10.1080/03610918.2018.1425445 ◽

2018 ◽

Vol 48 (6) ◽

pp. 1891-1900

Author(s):

Jiting Huang ◽

Peixin Zhao

Keyword(s):

Variable Selection ◽

Instrumental Variable ◽

Linear Models ◽

Selection For ◽

Endogenous Covariates

Variable selection for high-dimensional generalized linear models with the weighted elastic-net procedure

Journal of Applied Statistics ◽

10.1080/02664763.2015.1078300 ◽

2015 ◽

Vol 43 (5) ◽

pp. 796-809 ◽

Cited By ~ 17

Author(s):

Xiuli Wang ◽

Mingqiu Wang

Keyword(s):

Variable Selection ◽

Linear Models ◽

Elastic Net ◽

High Dimensional ◽

Variable Selection for Marginal Longitudinal Generalized Linear Models

Biometrics ◽

10.1111/j.1541-0420.2005.00331.x ◽

2005 ◽

Vol 61 (2) ◽

pp. 507-514 ◽

Cited By ~ 36

Author(s):

Eva Cantoni ◽

Joanna Mills Flemming ◽

Elvezio Ronchetti

Keyword(s):

Variable Selection ◽

Linear Models ◽

Generalized Empirical Likelihood Inference in Generalized Linear Models for Longitudinal Data

Communication in Statistics- Theory and Methods ◽

10.1080/03610926.2012.719987 ◽

2014 ◽

Vol 43 (18) ◽

pp. 3893-3904 ◽

Cited By ~ 1

Author(s):

Ruiqin Tian ◽

Liugen Xue

Keyword(s):

Longitudinal Data ◽

Empirical Likelihood ◽

Linear Models ◽

Likelihood Inference ◽

Generalized Empirical Likelihood

Variable selection for multivariate generalized linear models

Journal of Applied Statistics ◽

10.1080/02664763.2013.839640 ◽

2013 ◽

Vol 41 (2) ◽

pp. 393-406 ◽

Cited By ~ 2

Author(s):

Xiaoguang Wang ◽

Junhui Fan

Keyword(s):

Variable Selection ◽

Linear Models ◽

Consistency of hyper-$g$-prior-based Bayesian variable selection for generalized linear models

Brazilian Journal of Probability and Statistics ◽

10.1214/15-bjps299 ◽

2016 ◽

Vol 30 (4) ◽

pp. 691-709 ◽

Cited By ~ 3

Author(s):

Ho-Hsiang Wu ◽

Marco A. R. Ferreira ◽

Matthew E. Gompper

Keyword(s):

Variable Selection ◽

Linear Models ◽

Bayesian Variable Selection ◽

Selection For ◽

G Prior

Springer Proceedings in Mathematics & Statistics - Bayesian Statistics from Methods to Models and Applications ◽

Bayesian Variable Selection for Generalized Linear Models Using the Power-Conditional-Expected-Posterior Prior

10.1007/978-3-319-16238-6_6 ◽

2015 ◽

pp. 59-73

Author(s):

Konstantinos Perrakis ◽

Dimitris Fouskakis ◽

Ioannis Ntzoufras

Keyword(s):

Variable Selection ◽

Linear Models ◽

Bayesian Variable Selection ◽

Automatic variable selection for longitudinal generalized linear models

Computational Statistics & Data Analysis ◽

10.1016/j.csda.2012.12.015 ◽

2013 ◽

Vol 61 ◽

pp. 174-186 ◽

Cited By ~ 16

Author(s):

Gaorong Li ◽

Heng Lian ◽

Sanying Feng ◽

Lixing Zhu

Keyword(s):

Variable Selection ◽

Linear Models ◽

Smoothed empirical likelihood inference and variable selection for quantile regression with nonignorable missing response

Computational Statistics & Data Analysis ◽

10.1016/j.csda.2019.106888 ◽

2020 ◽

Vol 144 ◽

pp. 106888

Author(s):

Ting Zhang ◽

Lei Wang

Keyword(s):

Variable Selection ◽

Quantile Regression ◽

Empirical Likelihood ◽

Likelihood Inference ◽

Missing Response ◽

Selection For ◽

Smoothed Empirical Likelihood ◽

Nonignorable Missing