Model selection and structure specification in ultra-high dimensional generalised semi-varying coefficient models
From MaRDI portal
Publication:892254
DOI10.1214/15-AOS1356zbMath1327.62262arXiv1510.08683OpenAlexW2221963167MaRDI QIDQ892254
Wenyang Zhang, Yuan Ke, Degui Li
Publication date: 18 November 2015
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1510.08683
Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20)
Related Items (17)
Smooth-threshold estimating equations for varying coefficient partially nonlinear models based on orthogonality-projection method ⋮ Sparse Learning and Structure Identification for Ultrahigh-Dimensional Image-on-Scalar Regression ⋮ A reproducing kernel Hilbert space approach to high dimensional partially varying coefficient model ⋮ Model detection and estimation for varying coefficient panel data models with fixed effects ⋮ Sparsity identification in ultra-high dimensional quantile regression models with longitudinal data ⋮ The consistency of model selection for dynamic Semi-varying coefficient models with autocorrelated errors ⋮ Variable selection for partially varying coefficient model based on modal regression under high dimensional data ⋮ Variational inference for varying-coefficient model ⋮ Variable-dependent partial dimension reduction ⋮ Model selection and structure specification in ultra-high dimensional generalised semi-varying coefficient models ⋮ Time-varying forecast combination for high-dimensional data ⋮ Nonlinear Factor‐Augmented Predictive Regression Models with Functional Coefficients ⋮ Semiparametric model for covariance regression analysis ⋮ Varying coefficient functional autoregressive model with application to the U.S. treasuries ⋮ Composite Coefficient of Determination and Its Application in Ultrahigh Dimensional Variable Screening ⋮ SiZer inference for generalized varying coefficient models ⋮ Nonparametric homogeneity pursuit in functional-coefficient models
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Sure independence screening in generalized linear models with NP-dimensionality
- Nearly unbiased variable selection under minimax concave penalty
- The Adaptive Lasso and Its Oracle Properties
- Nonparametric independence screening and structure identification for ultra-high dimensional longitudinal data
- Statistics for high-dimensional data. Methods, theory and applications.
- Maximal spacings in several dimensions
- A semiparametric model for cluster data
- Model selection and structure specification in ultra-high dimensional generalised semi-varying coefficient models
- One-step sparse estimates in nonconcave penalized likelihood models
- The sparsity and bias of the LASSO selection in high-dimensional linear regression
- Simultaneous confidence band and hypothesis test in generalised varying-coefficient models
- Statistical estimation in varying coefficient models
- Least angle regression. (With discussion)
- Simultaneous analysis of Lasso and Dantzig selector
- On the adaptive elastic net with a diverging number of parameters
- Asymptotic properties of bridge estimators in sparse high-dimensional regression models
- New efficient estimation and variable selection methods for semiparametric varying-coefficient partially linear models
- Variable selection in semiparametric regression modeling
- Variable selection using MM algorithms
- Simultaneous Confidence Bands and Hypothesis Testing in Varying-coefficient Models
- Local Rank Inference for Varying Coefficient Models
- Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Additive Models
- A Semiparametric Threshold Model for Censored Longitudinal Data Analysis
- Variable selection and estimation in high-dimensional varying-coefficient models
- Extended Bayesian information criteria for model selection with large model spaces
- On varying-coefficient independence screening for high-dimensional varying-coefficient models
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Efficient Estimation and Inferences for Varying-Coefficient Models
- Feature Selection for Varying Coefficient Models With Ultrahigh-Dimensional Covariates
- Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Varying Coefficient Models
- Shrinkage Estimation of the Varying Coefficient Model
- Statistical Estimation in Generalized Multiparameter Likelihood Models
- Nonconcave Penalized Likelihood With NP-Dimensionality
- Asymptotic oracle properties of SCAD-penalized least squares estimators
- Variable Selection in Nonparametric Varying-Coefficient Models for Analysis of Repeated Measurements
- Model Selection and Estimation in Regression with Grouped Variables
This page was built for publication: Model selection and structure specification in ultra-high dimensional generalised semi-varying coefficient models