Results 71 to 80 of about 149 (141)

FUNCTIONAL SUFFICIENT DIMENSION REDUCTION THROUGH AVERAGE FRÉCHET DERIVATIVES. [PDF]

Ann Stat, 2022
Lee KY, Li L.
europepmc   +1 more source

Optimal ridge estimation in the restricted logistic semiparametric regression models using generalized cross-validation. [PDF]

J Appl Stat
Roozbeh M.
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  

Nonparametric Inference of Conditional Expectile Functions in Large-Scale Time Series Data With Improved Efficiency. [PDF]

J Time Ser Anal
Zhang F, Zhong PS.
europepmc   +1 more source

Nonparametric lack-of-fit tests for parametric mean-regression models with censored data

We developed two kernel smoothing based tests of a parametric mean-regression model against a nonparametric alternative when the response variable is right-censored.
Patilea, V., Lopez, O.
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

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

CLASSIFICATION WITH A REJECT OPTION USING A HINGE LOSS

, 2008
. We consider the problem of binary classification where the classifier can, for a particular cost, choose not to classify an observation. Just as in the conventional classification problem, minimization of the sample average of the cost is a difficult ...
H. Wegkamp, Peter L. Bartlett, Marten
core  

Adaptive exact recovery in sparse nonparametric models. [PDF]

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

A note on the Bayes factor in a semiparametric regression model

In this paper, we consider a semiparametric regression model where the unknown regression function is the sum of parametric and nonparametric parts. The parametric part is a finite-dimensional multiple regression function whereas the nonparametric part ...
Choi, Taeryon, Lee, Jaeyong, Roy, Anindya   +2 more
core