Tuning Parameter Selection in the LASSO with Unspecified Propensity

DOI10.1007/978-3-319-69416-0_7zbMath1402.62166OpenAlexW2787152891MaRDI QIDQ4556969

Yang Yang, Jiwei Zhao

Publication date: 28 November 2018

Published in: New Advances in Statistics and Data Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-69416-0_7

zbMATH Keywords

parameter selectionLASSO

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Statistical ranking and selection procedures (62F07)

Related Items (1)

Statistical methods without estimating the missingness mechanism: a discussion of ‘statistical inference for nonignorable missing data problems: a selective review’ by Niansheng Tang and Yuanyuan Ju

Uses Software

• glmnet

Cites Work

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• Nuisance parameter elimination for proportional likelihood ratio models with nonignorable missingness and random truncation
• Tuning parameter selectors for the smoothly clipped absolute deviation method
• Tuning Parameter Selection in High Dimensional Penalized Likelihood
• Bayesian survival analysis

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