Design and analysis of computer experiments with quantitative and qualitative inputs: A selective review

Computer experiment refers to the study of complex systems by using computer simulations to emulate the physical system. Design and analysis of computer experiments have attracted great attention in past decades. However, many computer experiments involve not only quantitative inputs, but also qualitative inputs, which make the design and analysis more challenging. The Latin hypercube design and its variants are widely used in computer experiments, but mainly for the quantitative inputs. Constructing desirable emulators for computer experiments with qualitative inputs also remains a challenging problem due to the discrete nature of qualitative inputs. In this review, we describe a set of statistical approaches for design and analysis of computer experiments with both quantitative and qualitative factors. This article is categorized under: Fundamental Concepts of Data and Knowledge > Key Design Issues in Data Mining Algorithmic Development > Statistics