A nonlinear regression model is applied to several sets of enzyme kinetics data, treating the entire regression vector as the parameter of interest. The resulting marginal posterior distributions are ...

Modern measurement techniques allow researchers to gather ever more data in less time. In many cases, however, the primary or raw data have to be further analyzed, be it for the verification of a ...

Under general conditions given here, the least squares estimator for the parameters of a misspecified nonlinear model converge strongly to the parameters of a (weighted) least squares approximation to ...