A Robust Consistent Information Criterion for Model Selection Based on Empirical Likelihood
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Publication:5089442
DOI10.5705/ss.202020.0254OpenAlexW3174472388MaRDI QIDQ5089442
Rongling Wu, Ming Wang, Chixiang Chen, Run-Ze Li
Publication date: 19 July 2022
Published in: Statistica Sinica (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2006.13281
Cites Work
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- Doubly Robust Estimation in Missing Data and Causal Inference Models
- Longitudinal data analysis using generalized linear models
- Consistent model selection criteria for quadratically supported risks
- The asymptotic effect of substituting estimators for parameters in certain types of statistics
- Estimating the dimension of a model
- Empirical likelihood and general estimating equations
- A new scope of penalized empirical likelihood with high-dimensional estimating equations
- Empirical likelihood based variable selection
- Penalized Generalized Estimating Equations for High-Dimensional Longitudinal Data Analysis
- Robust Estimation of Area Under ROC Curve Using Auxiliary Variables in the Presence of Missing Biomarker Values
- Penalized high-dimensional empirical likelihood
- Akaike's Information Criterion in Generalized Estimating Equations
- Extended Bayesian information criteria for model selection with large model spaces
- Empirical likelihood ratio confidence intervals for a single functional
- Estimation of Regression Coefficients When Some Regressors Are Not Always Observed
- Generalised information criteria in model selection
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Adjusting for Nonignorable Drop-Out Using Semiparametric Nonresponse Models
- Empirical‐likelihood‐based criteria for model selection on marginal analysis of longitudinal data with dropout missingness
- A new look at the statistical model identification
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