Switching nonparametric regression models

Nonlinear Nonparametric Regression Models

Almost all of the current nonparametric regression methods such as smoothing splines, generalized additive models and varying coefficients models assume a linear relationship when nonparametric functions are regarded as parameters. In this article, we propose a general class of nonlinear nonparametric models that allow nonparametric functions to act nonlinearly. They arise in many fields as eit...

Nonparametric estimation of a switching regression model

Nonparametric Regression

This article has no abstract.

Nonparametric Mixture of Regression Models.

Motivated by an analysis of US house price index data, we propose nonparametric finite mixture of regression models. We study the identifiability issue of the proposed models, and develop an estimation procedure by employing kernel regression. We further systematically study the sampling properties of the proposed estimators, and establish their asymptotic normality. A modified EM algorithm is ...

Mechanical models in nonparametric regression

A common motif in the expositions of spline-based methods in statistical smoothing or numerical interpolation is an allusion to mechanical analogies—motivated perhaps by a desire to provide some explanation why the resulting shapes ought to be regarded as “natural”. The univariate case has its Oxford English Dictionary reference to draftsman spline as “a flexible strip of wood or hard rubber us...