Regularization parameter selection for penalized empirical likelihood estimator

DOI10.1016/j.econlet.2019.02.011zbMath1417.62187OpenAlexW2916008461WikidataQ128337230 ScholiaQ128337230MaRDI QIDQ1741726

Tomohiro Ando, Naoya Sueishi

Publication date: 7 May 2019

Published in: Economics Letters (Search for Journal in Brave)

Full work available at URL: http://www.lib.kobe-u.ac.jp/repository/90005996.pdf

zbMATH Keywords

variable selectioninformation criterion

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Nonparametric estimation (62G05) Statistical aspects of information-theoretic topics (62B10)

Cites Work

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• Nearly unbiased variable selection under minimax concave penalty
• The Adaptive Lasso and Its Oracle Properties
• Nonparametric likelihood ratio model selection tests between parametric likelihood and moment condition models
• Estimating the dimension of a model
• Empirical likelihood and general estimating equations
• A new scope of penalized empirical likelihood with high-dimensional estimating equations
• High dimensional generalized empirical likelihood for moment restrictions with dependent data
• On the ``degrees of freedom of the lasso
• Penalized empirical likelihood and growing dimensional general estimating equations
• Shrinkage Tuning Parameter Selection with a Diverging number of Parameters
• General Saddlepoint Approximations of Marginal Densities and Tail Probabilities
• The influence function of penalized regression estimators
• LASSO-TYPE GMM ESTIMATOR
• Regression and time series model selection in small samples
• Generalised information criteria in model selection
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• GENERALIZED EMPIRICAL LIKELIHOOD–BASED MODEL SELECTION CRITERIA FOR MOMENT CONDITION MODELS
• Higher-Order Infinitesimal Robustness
• Regularization and Variable Selection Via the Elastic Net
• Estimation of Sparse Structural Parameters with Many Endogenous Variables
• Consistent model and moment selection procedures for GMM estimation with application to dynamic panel data models

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