Variable selection in partially time-varying coefficient models

DOI10.1080/10485250902912694zbMath1165.62031OpenAlexW1966655817MaRDI QIDQ5321918

Zheng Yan Lin, Jia Chen, Degui Li

Publication date: 16 July 2009

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485250902912694

zbMATH Keywords

semiparametric regressionoracle propertytime-varying coefficients modelpenalised least squaresprofile local linear technique

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Monte Carlo methods (65C05)

Related Items

Statistical inference in partially time-varying coefficient models ⋮ Simultaneous variable selection and structural identification for time‐varying coefficient models ⋮ A Stratified Penalized Kernel Method for Semiparametric Variable Labeling and Estimation of Multi-Output Time-Varying Coefficient Models for Nonstationary Time Series ⋮ Semiparametric model building for regression models with time-varying parameters ⋮ Variable selection for partially time-varying coefficient error-in-variables models

Cites Work

• Unnamed Item
• Trending time-varying coefficient time series models with serially correlated errors
• Profile likelihood inferences on semiparametric varying-coefficient partially linear models
• One-step sparse estimates in nonconcave penalized likelihood models
• Profile-kernel likelihood inference with diverging number of parameters
• Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation
• Heuristics of instability and stabilization in model selection
• Central limit theorem for linear processes
• Trending time series and macroeconomic activity: Some present and future challenges
• Generalized likelihood ratio statistics and Wilks phenomenon
• The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
• Variable selection in semiparametric regression modeling
• Nonlinear Time Series
• Efficient estimation for semivarying-coefficient models
• Quasi-likelihood Estimation in Semiparametric Models
• Ideal spatial adaptation by wavelet shrinkage
• Generalized Partially Linear Single-Index Models
• Semiparametric Regression
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Semiparametric Non-Linear Time Series Model Selection
• Semiparametric Regression for the Applied Econometrician
• A Statistical View of Some Chemometrics Regression Tools