Estimating Michaelis‐Menten or Langmuir Isotherm Constants by Weighted Nonlinear Least Squares

Abstract

Abstract We derive a nonlinear least squares fitting method for determining either Michaelis‐Menten equation or Langmuir adsorption isotherm constants from experimental data. Data points can be weighted unequally if their relative precisions are known. Comparison of this method with the commonly used linearization methods, using simulated data sets containing normally distributed random errors, showed that this method yields more accurate and precise estimates of the constants than any of the linearizations. A short BASIC program to facilitate computation is presented.