Computer simulation is often used to study complex physical and engineering processes. While a computer simulator can often be viewed as an inexpensive way to gain insight into a system, it can stillâ€¦ (More)

For many expensive deterministic computer simulators, the outputs do not have replication error and the desired metamodel (or statistical emulator) is an interpolator of the observed data.â€¦ (More)

European journal of population = Revue europeenneâ€¦

1999

A two-period stochastic model of fertility behavior was developed in order to provide an explanation for the staggering decrease in birth rates in former Soviet Republics and Eastern Europeanâ€¦ (More)

Constrained blackbox optimization is a di fficult problem, with most approaches coming from the mathematical programming literature. The statistical literature is sparse, especially in addressingâ€¦ (More)

Constrained blackbox optimization is a difficult problem, with most approaches coming from the mathematical programming literature. The statistical literature is sparse, especially in addressingâ€¦ (More)

Gaussian process (GP) models are commonly used statistical metamodels for emulating expensive computer simulators. Fitting a GP model can be numerically unstable if any pair of design points in theâ€¦ (More)

Gaussian Process (GP) models are popular statistical surrogates used for emulating computationally expensive computer simulators. The quality of a GP model fit can be assessed by a goodness of fitâ€¦ (More)

Identifying promising compounds from a vast collection of feasible compounds is an important and yet challenging problem in pharmaceutical industry. An efficient solution to this problem will helpâ€¦ (More)

Remote sensing methods have extensively been applied in many areas, for instance, hydrological modeling, wildlife habitat modeling, forest degradation monitoring, wetland biodiversity conservationâ€¦ (More)