Surrogate modeling, also called metamodeling, has evolved and been extensively used
over the past decades. A wide variety of methods and tools have been introduced for …

In many fields, such as environmental risk assessment, agronomic system behavior,
aerospace engineering, and nuclear safety, mathematical models turned into computer code …

Chemists routinely create models of reaction systems to understand reaction mechanisms,
kinetic properties, process yields under various operating conditions, or the impact of …

Decision tree ensembles are an extremely popular tool for obtaining high-quality predictions
in nonparametric regression problems. Unmodified, however, many commonly used …

The analysis of many physical and engineering problems involves running complex
computational models (simulation models, computer codes). With problems of this type, it is …

Genome-wide prediction of complex traits has become increasingly important in animal and
plant breeding, and is receiving increasing attention in human genetics. Most common …

Partially linear models provide a useful class of tools for modeling complex data by naturally
incorporating a combination of linear and nonlinear effects within one framework. One key …

Moment-independent sensitivity methods are attracting increasing attention among
practitioners, since they provide a thorough way of investigating the sensitivity of model …

The environmental costs of intensive farming activities are often under-estimated or not
traded by the market, even though they play an important role in addressing future society's …

Metamodelling is an increasingly more popular approach for alleviating the computational
burden associated with computationally intensive optimization/management problems in …