A New Robust Method for Nonlinear Regression.

ABSTRACT:

Background

When outliers are present, the least squares method of nonlinear regression performs poorly. The main purpose of this paper is to provide a robust alternative technique to the Ordinary Least Squares nonlinear regression method. This new robust nonlinear regression method can provide accurate parameter estimates when outliers and/or influential observations are present.

Method

Real and simulated data for drug concentration and tumor size-metastasis are used to assess the performance of this new estimator. Monte Carlo simulations are performed to evaluate the robustness of our new method in comparison with the Ordinary Least Squares method.

Results

In simulated data with outliers, this new estimator of regression parameters seems to outperform the Ordinary Le

SUBMITTER: Tabatabai MA 

PROVIDER: S-EPMC4501042 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature