lhsgeneral(pd,corre​lation,n)

版本 1.2.0.0 (3.5 KB) 作者: Iman
This function implements Latin hypercube sampling method for correlated random variables.
1.0K 次下载
更新时间 2017/3/7

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This function is developed to generate different realizations of correlated random variables using Latin hypercube sampling method. To learn more about this function, please watch the following tutorial:
https://www.youtube.com/watch?v=pVgKwqN621s
Please watch the following short tutorials to quickly learn random sampling (Monte Carlo Vs. Latin hypercube sampling):
Random Sampling - Tutorial 1 - Introduction
https://www.youtube.com/watch?v=kKpqGcCUFF8&index=1&list=PLJ-OcUCIty7fJQiAdjMjBiCbBkT563iSY
Random Sampling - Tutorial 2 - Monte Carlo
https://www.youtube.com/watch?v=M9hjdX97Z3s&index=2&list=PLJ-OcUCIty7fJQiAdjMjBiCbBkT563iSY

Random Sampling - Tutorial 3 - Monte Carlo Example
https://www.youtube.com/watch?v=mATm9eCtJaQ&index=3&list=PLJ-OcUCIty7fJQiAdjMjBiCbBkT563iSY

Random Sampling - Tutorial 4 - Latin Hypercube Sampling
https://www.youtube.com/watch?v=H0RZ1uezuuw&index=4&list=PLJ-OcUCIty7fJQiAdjMjBiCbBkT563iSY

Random Sampling - Tutorial 5 - Monte Carlo Vs. Latin Hypercube Sampling
https://www.youtube.com/watch?v=2u4YlhrrDQE&index=5&list=PLJ-OcUCIty7fJQiAdjMjBiCbBkT563iSY

Please subscribe to my signal processing channel to see more tutorials:
https://www.youtube.com/channel/UCVkatNMgkEdpWLhH0kBqqLw

Acknowledgements:
This submission is developed for 2060 Project at the Institute for Integrated Energy Systems at the University of Victoria, Canada. The project has been funded by Pacific Institute for Climate Solutions, Natural Resources Canada and Natural Sciences and Engineering Research Council of Canada. This funding is gratefully acknowledged.

引用格式

Iman (2024). lhsgeneral(pd,correlation,n) (https://www.mathworks.com/matlabcentral/fileexchange/56384-lhsgeneral-pd-correlation-n), MATLAB Central File Exchange. 检索来源 .

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版本 已发布 发行说明
1.2.0.0

description update.
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adding youtube channel
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bug fix. Very special thanks to EAnane for finding and fixing the issue!
Big update on the algorithm used.
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1.1.0.0

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1.0.0.0

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