Computational Experience With Confidence Regions and Confidence Intervals for Nonlinear Least Squares

Technometrics ◽  
1987 ◽  
Vol 29 (1) ◽  
pp. 67-82 ◽  
Author(s):  
Janet R. Donaldson ◽  
Robert B. Schnabel
2019 ◽  
Vol 32 (10) ◽  
pp. 471-479 ◽  
Author(s):  
Kresten Lindorff-Larsen

Abstract The linear extrapolation method to determine protein stability from denaturant-induced unfolding experiments is based on the observation that the free energy of unfolding is often a linear function of the denaturant concentration. The value in the absence of denaturant is then estimated by extrapolation from this linear relationship. Parameters and their confidence intervals are typically estimated by nonlinear least-squares regression. We have compared different methods for calculating confidence intervals and found that a simple method based on linear theory gives accurate results. We have also compared three different parameterizations of the linear extrapolation method and show that the most commonly used form is problematic since the stability and m-value are correlated in the nonlinear least-squares analysis. Parameter correlation can in some cases causes problems in the estimation of confidence intervals and regions and should be avoided when possible. Two alternative parameterizations show much less correlation between parameters.


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