On the computational methods in non-linear design of experiments

In this paper the non-linear problem is discussed, for point and interval computational estimation. For the interval estimation an adjusted formulation is discussed due to Beale’s measure of non-linearity. The non-linear experimental design problem is regarded when the errors of observations are assumed i.i.d. and normally distributed as usually. The sequential approach is adopted. The average-per-observation information matrix is adopted to the developed theoretical approach. Different applications are discussed and we provide evidence that the sequential approach might be the panacea for solving a non-linear optimal experimental design problem.info:eu-repo/semantics/publishedVersio

Asymptotic statistical results: theory and practice

The target of this paper is to discuss the existent difference of Asymptotic Theory in Statistics comparing to Mathematics. There is a need for a limiting distribution in Statistics, usually the Normal one. Adopting the sequential principle the first-order autoregression model and the stochastic approximation are referred for their particular interest for asymptotic results.info:eu-repo/semantics/publishedVersio