Structured Ultrahigh Dimensional Multiple-Index Models with Efficient Estimation in Computation And Theory

DOI10.5705/ss.202021.0009OpenAlexW4200012505WikidataQ114013802 ScholiaQ114013802MaRDI QIDQ6092965

No author found.

Publication date: 23 November 2023

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.5705/ss.202021.0009

zbMATH Keywords

maximum likelihood estimationvariable selectionhigh-dimensional covariatessemiparametrical efficiencystructured multiple-index models

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Model-Free Feature Screening for Ultrahigh-Dimensional Data
• Nearly unbiased variable selection under minimax concave penalty
• A unified approach to model selection and sparse recovery using regularized least squares
• Local partial-likelihood estimation for lifetime data
• Nonparametric stochastic frontiers: a local maximum likelihood approach
• Formulation and estimation of stochastic frontier production function models
• Semiparametric estimation of conditional heteroscedasticitity via single-index modeling
• Extended Bayesian information criteria for model selection with large model spaces
• Generalized Partially Linear Single-Index Models
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Doubly Robust and Efficient Estimators for Heteroscedastic Partially Linear Single-Index Models Allowing high Dimensional Covariates
• Regularization and Variable Selection Via the Elastic Net
• Sparse single-index model
• A Multiple-Index Model and Dimension Reduction
• Partial linear varying multi-index coefficient model for integrative gene-environment interactions
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item