منابع مشابه
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 ...
متن کاملQuantile Estimation with Latin Hypercube Sampling
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متن کاملLatin 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 ...
متن کاملWind Power Forecasting Based on Extended Latin Hypercube Sampling
With the rise of distributed generation, such as wind power and photovoltaic (PV), it is necessary to consider the effect of distributed generation’s output randomness. Using the method of Latin hypercube sampling (LHS) can effectively fit output scenario. Considering the sampling number of conventional LHS (CLHS) must be fixed in advance, LHS(ELHS) can be Extended to predict wind power. The sa...
متن کاملCommodity 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 ...
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ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 1996
ISSN: 0090-5364
DOI: 10.1214/aos/1069362310