Results 31 to 40 of about 101,932 (253)
Variational Multiscale Nonparametric Regression: Algorithms and Implementation
Many modern statistically efficient methods come with tremendous computational challenges, often leading to large-scale optimisation problems. In this work, we examine such computational issues for recently developed estimation methods in nonparametric ...
Miguel del Alamo +3 more
doaj +1 more source
Tests for Independence in Nonparametric Regression [PDF]
Consider the nonparametric regression model Y = m(X)+e, where the function m is smooth, but unknown.We construct tests for the independence of e and X, based on n independent copies of (X; Y ).The testing procedures are based on differences of neighboring Y 's.We establish asymptotic results for the proposed tests statistics, investigate their finite ...
Einmahl, J.H.J., Keilegom, I. van
openaire +7 more sources
Nonparametric Tests for Shifts in Nonlinear Regression [PDF]
We propose nonparametric test statistics for the at most one change point (AMOC) problem in the regression function of a nonlinear regression model.
Abd-Elnaser Abd-Rabou
doaj +1 more source
Bayesian nonparametric monotone regression
AbstractIn many applications there is interest in estimating the relation between a predictor and an outcome when the relation is known to be monotone or otherwise constrained due to the physical processes involved. We consider one such application‐inferring time‐resolved aerosol concentration from a low‐cost differential pressure sensor. The objective
Ander Wilson +3 more
openaire +5 more sources
Test for Linearity in Non-Parametric Regression Models
The problem of checking the linearity of a regression relationship is addressed. The test uses nonparametric estimation techniques. The null hypothesis is that the regression function is linear; it is tested against the non-specic alternatives hypotheses.
Khedidja Djaballah-Djeddour +1 more
doaj +3 more sources
Nonparametric Regression Estimation for Circular Data
Non-parametric regression with a circular response variable and a unidimensional linear regressor is a topic which was discussed in the literature.
Andrea Meilán-Vila +3 more
doaj +1 more source
Minimally Biased Nonparametric Regression and Autoregression
A nonparametric regression estimator is introduced which adapts to the smoothness of the unknown function being estimated. This property allows the new estimator to automatically achieve minimal bias over a large class of locally smooth functions ...
Timothy L. McMurry +1 more
doaj +1 more source
Universal Local Linear Kernel Estimators in Nonparametric Regression
New local linear estimators are proposed for a wide class of nonparametric regression models. The estimators are uniformly consistent regardless of satisfying traditional conditions of dependence of design elements.
Yuliana Linke +5 more
doaj +1 more source
Local Linear Regression Estimator on the Boundary Correction in Nonparametric Regression Estimation
The precision and accuracy of any estimation can inform one whether to use or not to use the estimated values. It is the crux of the matter to many if not all statisticians.
Langat Reuben Cheruiyot
doaj +1 more source
qgam: Bayesian Nonparametric Quantile Regression Modeling in R
Generalized additive models (GAMs) are flexible non-linear regression models, which can be fitted efficiently using the approximate Bayesian methods provided by the mgcv R package.
Matteo Fasiolo +4 more
doaj +1 more source

