The Effects of Nonlinearity in Regression Models. Part 2: A Function Describing Nonlinearity.

Abstract

In a previous paper (Draper and Shaw, 1973), the authors provided a way of assessing nonlinearity in nonlinear estimation problems with n observations and p parameters via a function F bar(p,n-p, 1-alpha). This function measured the average deviation from linearity around the usual linearized (1-alpha) F bar(p,n-p, a-alpha) as a function of F(p,n-p,1-alpha), and demonstrate that the coefficients convey, in an intuitively sensible manner, information about the nonlinearity of the model. (Modified author abstract)

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1974
Accession Number
AD0779376

Entities

People

  • Douglas E. Shaw
  • Norman Richard Draper

Organizations

  • University of Wisconsin–Madison

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Coefficients
  • Linearity
  • Observation

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Calculus or Mathematical Analysis
  • Neuroscience