The models used in small-area inference often involve unobservable random effects. While
this can significantly improve the adaptivity and flexibility of a model, it also increases the …

Differential Evolution (DE) has become one of the leading metaheuristics in the class of
Evolutionary Algorithms, which consists of methods that operate off of survival-of-the-fittest …

Research in optimal experimental design has a long history and dates back as early as 1918
in a seminal paper by Smith (1918) and probably earlier. This chapter discusses algorithms …

We consider a measurement constrained supervised learning problem, that is, (i) full sample
of the predictors are given; (ii) the response observations are unavailable and expensive to …

… In a recent article, Datta, Hall, and Mandal showed that if the … The work of Datta, Hall, and
Mandal is most useful when the … approach in Datta, Hall, and Mandal, in this article we consider …

In this article, we propose an efficient approach to find optimal experimental designs for
event-related functional magnetic resonance imaging (ER-fMRI). We consider multiple objectives…

The use of conventional petroleum‐based plastics in many applications poses the risk of
contamination, potentially causing infection when used in medical applications, and …

The objective of this study was to evaluate the effects of gestational exposure to low doses of
bisphenol A (BPA), bisphenol S (BPS), and bisphenol F (BPF) on pregnancy outcomes and …

Identifying optimal designs for generalized linear models with a binary response can be a
challenging task, especially when there are both discrete and continuous independent factors …

Bisphenol A (BPA) and Diethylhexyl Phthalate (DEHP) are well-studied endocrine disrupting
chemicals (EDCs), however, the effects of mixtures of these EDCs are not. To assess the …