Results 81 to 90 of about 233 (155)

SCAD-Penalized Regression in High-Dimensional Partially Linear Models

, 2006
Summary. We consider the problem of simultaneous variable selection and estimation in partially linear models with a divergent number of covariates in the linear part, under the assumption that the vector of regression coefficients is sparse.
Huiliang Xie, Jian Huang
core  

Variable selection for partially linear models via Bayesian subset modeling with diffusing prior. [PDF]

J Multivar Anal, 2021
Wang J, Cai X, Li R.
europepmc   +1 more source

Nonparametric regression with discrete covariate and missing values

, 2011
S. Chen, C. Tang
semanticscholar   +1 more source

Multi-sample test based on bootstrap methods for second order stochastic dominance

, 2014
Zhang, Jianling, Zhongzhan
semanticscholar   +1 more source

Adaptive exact recovery in sparse nonparametric models. [PDF]

Stat Inference Stoch Process
Stepanova N, Turcicova M.
europepmc   +1 more source

Learning from dependent observations

In most papers establishing consistency for learning algorithms it is assumed that the observations used for training are realizations of an i.i.d. process. In this paper we go far beyond this classical framework by showing that support vector machines (
Scovel, Clint, Hush, Don, Steinwart, Ingo   +2 more
core  

Integrative analysis of high-dimensional quantile regression with contrasted penalization. [PDF]

J Appl Stat
Ren P, Liu X, Zhang X, Zhan P, Qiu T.
europepmc   +1 more source

Spatiotemporal Heterogeneity Learning: Generalized SpatioTemporal Semi-Varying Coefficient Models With Structure Identification. [PDF]

J Time Ser Anal
Gu Z, Li X, Wang G, Wang L.
europepmc   +1 more source

Local polynomial regression for pooled response data. [PDF]

J Nonparametr Stat, 2020
Wang D, Mou X, Li X, Huang X.
europepmc   +1 more source

Local linear regression for functional predictor and scalar response

The aim of this work is to introduce a new nonparametric regression technique in the context of functional covariate and scalar response. We propose a local linear regression estimator and study its asymptotic behaviour.
Grané, Aurea, Baíllo, Amparo
core