Taking Variable Correlation into Consideration during Parameter Estimation

Abstract

Variable correlations are usually neglected during parameter estimation. Very frequently these are gross assumptions and may potentially lead to inadequate interpretation of final estimation results. For this reason, variable correlation and model parameters are sometimes estimated simultaneously in certain parameter estimation procedures. It is shown, however, that usually taking variable correlation into consideration during parameter estimation may be inadequate and unnecessary, unless independent experimental analysis of measurement procedures is carried out

Lumped kinetics and acute toxicity of intermediates in the ozonation of phenol in saline media

“…Kinetic and adsorption constants were estimated by a least squares regression quasiNewton algorithm [33,34]. change was observed.…”

Epoxidation Kinetics of High-Linolenic Triglyceride Catalyzed by Solid Acidic-Ion Exchange Resin

“…20,23 had shown the existence of strong correlation of kinetic parameters in mathematical models containing more than one temperature-dependent kinetic constant. Such correlation makes the task of precise estimation of different kinetic parameters more onerous 24,25 . In such cases, re-parametrized form of Arrhenius equation is known to significantly reduce computational effort by reducing the correlation between parameters 26 .…”

Modeling an annular flow tubular reactor

“…(21)). The parameters are correlated, thus a maximum likelihood procedure was used, the ESTIMA software (Santos and Pinto, 1998). At this step, no oscillations were considered; therefore the model described the curve inclination, and its proximity to a PFR model.…”