The generalization of Latin hypercube sampling

Latin hypercube sampling with multidimensional uniformity

Complex models can only be realized a limited number of times due to large computational requirements. Methods exist for generating input parameters for model realizations including Monte Carlo simulation (MCS) and Latin hypercube sampling (LHS). Recent algorithms such as maximinLHS seek to maximize the minimum distance between model inputs in the multivariate space. A novel extension of Latin ...

Quantile Estimation with Latin Hypercube Sampling

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Latin Hypercube Sampling in Bayesian Networks

We propose a scheme for producing Latin hypercube samples that can enhance any of the existing sampling algorithms in Bayesian networks. We test this scheme in combination with the likelihood weighting algorithm and show that it can lead to a significant improvement in the convergence rate. While performance of sampiing algorithms in general depends on the numerical properties of a network, in ...

Commodity price uncertainty propagation in open-pit mine production planning by Latin hypercube sampling method

Production planning of an open-pit mine is a procedure during which the rock blocks are assigned to different production periods in a way that leads to the highest net present value (NPV) subject to some operational and technical constraints. This process becomes much more complicated by incorporation of the uncertainty existing in the input parameters. The commodity price uncertainty is among ...

2 the Wd of Random Sampling and Latin Hypercube