Optimal Experiment Design, Latin Hypercube
Latin hypercube design is a way to generate design points that can spread observations evenly over the range of each input variable. For a Latin hypercube design of size n, the domain of each input variable is divided into n intervals and a set of n design points is chosen in such a way that the projections of design points onto each factor consist of exactly one observation for each interval.
Latin hypercube design was first introduced by McKay (McKay et al. 1979) for computer experiments ( Partial Differntial Equations, Numerical Methods and Simulations), by which experimentations are performed in computers using physical models and finite-element-based methods (Santner et al. 2003). Computer experiments are widely used in biology. For example, computer simulations are conducted to study the adhesion of a cell to a surface in flow (Chang et al. 2000). Latin hypercube designs are shown to be desirable...
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