When setting up a computer experiment, it has become a standard practice to select the
inputs spread out uniformly across the available space. These so-called space-filling …

In the present paper we provide a thorough study of small sample and asymptotical
comparisons of the efficiencies of equidistant designs taking into account both the …

This paper discusses the problem of determining optimal designs for regression models,
when the observations are dependent and taken on an interval. A complete solution of this …

In the common linear regression model the problem of determining optimal designs for least
squares estimation is considered in the case where the observations are correlated. A …

The aim of this paper is to provide guidelines for the statistically efficient estimation of
parameters of a modified Arrhenius model for chemical kinetics. A modified Arrhenius model …

A single purpose design may be quite inefficient for handling a real‐life problem. Therefore,
we often need to incorporate more than one design criterion and a common approach is …

Output from computer simulation experiments is often approximated as realizations of
correlated random fields. Consequently, the corresponding optimal design questions must …

This paper presents a new and efficient method for the construction of optimal designs for
regression models with dependent error processes. In contrast to most of the work in this …

In the paper, we solve the n-point optimal prediction design problem for the simplest
nontrivial finite discrete spectrum linear regression models with correlated observations. We …

The common linear regression model is given by y (x)= θ1f1 (x)+···+ θmfm (x)+ ε (x),(6.1)
where f1 (x),..., fm (x) are given linearly independent functions, ε (x) denotes a random error …