Results 31 to 40 of about 280,932 (148)

Nonparametric Regression Estimation for Multivariate Null Recurrent Processes

Econometrics, 2015
This paper discusses nonparametric kernel regression with the regressor being a \(d\)-dimensional \(\beta\)-null recurrent process in presence of conditional heteroscedasticity. We show that the mean function estimator is consistent with convergence rate
Biqing Cai, Dag Tjøstheim
doaj   +1 more source

Sparse Additive Models

, 2008
We present a new class of methods for high-dimensional nonparametric regression and classification called sparse additive models (SpAM). Our methods combine ideas from sparse linear modeling and additive nonparametric regression.
Lafferty, John, Liu, Han, Ravikumar, Pradeep, Wasserman, Larry   +3 more
core   +2 more sources

Outliers vs Robustness in Nonparametric Methods of Regression

Acta Universitatis Lodziensis. Folia Oeconomica, 2018
The article addresses the question of how robust methods of regression are against outliers in a given data set. In the first part, we presented the selected methods used to detect outliers.
Joanna Trzęsiok
doaj   +1 more source

Multi-Task Nonparametric Regression Under Joint Sparsity

IEEE Access
This study investigates a multi-task estimation under joint sparsity. We consider estimating multiple functions when functions of interest share common sparsity patterns.
Jae-Hwan Jhong, Gyeongmin Kim, Kwan-Young Bak   +2 more
doaj   +1 more source

Spatially-adaptive sensing in nonparametric regression

, 2013
While adaptive sensing has provided improved rates of convergence in sparse regression and classification, results in nonparametric regression have so far been restricted to quite specific classes of functions.
Bull, Adam D.
core   +1 more source

On concurvity in nonlinear and nonparametric regression models

Statistica, 2014
When data are affected by multicollinearity in the linear regression framework, then concurvity will be present in fitting a generalized additive model (GAM). The term concurvity describes nonlinear dependencies among the predictor variables.
Sonia Amodio, Massimo Aria, Antonio D’Ambrosio   +2 more
doaj   +1 more source

Fuzzy sets in nonparametric Bayes regression

, 2008
A simple Bayesian approach to nonparametric regression is described using fuzzy sets and membership functions. Membership functions are interpreted as likelihood functions for the unknown regression function, so that with the help of a reference prior ...
Angers, Jean-François, Delampady, Mohan
core   +1 more source

Powerful nonparametric checks for quantile regression [PDF]

, 2014
We address the issue of lack-of-fit testing for a parametric quantile regression. We propose a simple test that involves one-dimensional kernel smoothing, so that the rate at which it detects local alternatives is independent of the number of covariates.
Lavergne, Pascal, Maistre, Samuel, Patilea, Valentin   +2 more
core   +4 more sources

Confidence sets for nonparametric wavelet regression

, 2005
We construct nonparametric confidence sets for regression functions using wavelets that are uniform over Besov balls. We consider both thresholding and modulation estimators for the wavelet coefficients.
Genovese, Christopher R., Wasserman, Larry   +1 more
core   +2 more sources

Robust nonparametric estimation via wavelet median regression [PDF]

, 2008
In this paper we develop a nonparametric regression method that is simultaneously adaptive over a wide range of function classes for the regression function and robust over a large collection of error distributions, including those that are heavy-tailed,
Brown, Lawrence D., Cai, T. Tony, Zhou, Harrison H.   +2 more
core   +3 more sources