Accession Number : ADA186476

Title :   A Transformation/Weighting Model for Estimating Michaelis-Menten Parameters,

Corporate Author : NORTH CAROLINA UNIV AT CHAPEL HILL INST OF STATISTICS

Personal Author(s) : Carroll, Raymond J ; Cressie, Noel ; Ruppert, David

PDF Url : ADA186476

Report Date : Feb 1987

Pagination or Media Count : 29

Abstract : There has been considerable disagreement about how best to estimate the parameters in Michaelis-Menten models. This document points out that many fitting methods are based on different stochastic models, being weighted least squares estimates after appropriate transformation. The authors propose a flexible model which can be used to help determine the proper transformation and choice of weights. The method is illustrated by examples. Keywords: Nonlinear regression; Lineweaver Burke transformation.

Descriptors :   *WEIGHTING FUNCTIONS, ESTIMATES, LEAST SQUARES METHOD, MATHEMATICAL MODELS, FITTING FUNCTIONS(MATHEMATICS), PARAMETERS, NONLINEAR ANALYSIS, REGRESSION ANALYSIS, STOCHASTIC PROCESSES, WEIGHT

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE