Evaluating Quasi-Monte Carlo (QMC) algorithms in blocks decomposition of de-trended
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Abstract:
The length of equal minimal and maximal blocks has eected on logarithm-scale logarithm against sequential function on variance and bias of de-trended uctuation analysis, by using Quasi Monte Carlo(QMC) simulation and Cholesky decompositions, minimal block couple and maximal are founded which are minimum the summation of mean error square in Horest power.
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evaluating quasi-monte carlo (qmc) algorithms in blocks decomposition of de-trended
the length of equal minimal and maximal blocks has e ected on logarithm-scale logarithm against sequential function on variance and bias of de-trended uctuation analysis, by using quasi monte carlo(qmc) simulation and cholesky decompositions, minimal block couple and maximal are founded which are minimum the summation of mean error square in horest power.
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Journal title
volume 7 issue 4
pages 293- 299
publication date 2015-09-01
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