Exclusive Content & Downloads from ASQ

Illustrating How Science Can Be Incorporated into a Nonlinear Regression Model

Summary: We show the value of using available scientific knowledge in developing a data model for the simple example of drop heights of balls subject to drag. The science-based data model is a nonlinear regression model, where the mean is a solution to a differential equation. We contrast its analysis results with those from an empirical model. MATLAB code for fitting the science-based data model is also provided.

Anyone with a subscription, including Site and Enterprise members, can access this article.

Other Ways to Access content:

Join ASQ

Join ASQ as a Full member. Enjoy all the ASQ member benefits including access to many online articles.

  • Topics: Engineering
  • Keywords: Regression, Empirical model, Differential equations, Measurement error, Distribution,
  • Author: Hamada, M. S.; Higdon, D. M.; Abes, J.; Hills, C.; Peters, A. M.;
  • Journal: Quality Engineering