Nonlinear Regression withR

Nonlinear regression

Estimating nonlinear regression errors without doing regression

A method for estimating nonlinear regression errors and their distributions without performing regression is presented. Assuming continuity of the modeling function the variance is given in terms of conditional probabilities extracted from the data. For N data points the computational demand is N. Comparing the predicted residual errors with those derived from a linear model assumption provides...

Inference in Nonlinear Regression

This paper considers inference in a standard nonlinear regression model. We show that the model is non-regular in the sense that test statistics of interest exhibit a discontinuity in their limit distribution as a function of a parameter in the model. The discontinuity occurs when the coe¢ cient of a nonlinear regressor is zero. This paper establishes the asymptotic distributions of the least s...

Introduction to Nonlinear Regression

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...