Revised regional importance measures in the presence of epistemic and aleatory uncertainties

Two revised regional importance measures （RIMs）, that is, revised contribution to variance of sample mean （RCVSM） and re- vised contribution to variance of sample variance （RCVSV）, are defined herein by using the revised means of sample mean and sample variance, which vary with the reduced range of...

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Bibliographic Details
Published in:Science China. Physics, mechanics & astronomy mechanics & astronomy, 2015-01, Vol.58 (1), p.84-94
Main Authors: Cheng, Lei, Lu, ZhenZhou, Wu, DanQing
Format: Article
Language:English
Subjects:
Astronomy
Classical and Continuum Physics
Computation
Computational efficiency
Epistemology
Exact solutions
Mathematical analysis
Mathematical models
Observations and Techniques
Parameters
Physics
Physics and Astronomy
Polynomials
Regional
RIMS
Sample variance
Upper bounds
Variance
不确定性
二次多项式
修订
参数范围
样本均值
样本方差
计算成本
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Summary:Two revised regional importance measures （RIMs）, that is, revised contribution to variance of sample mean （RCVSM） and re- vised contribution to variance of sample variance （RCVSV）, are defined herein by using the revised means of sample mean and sample variance, which vary with the reduced range of the epistemic parameter. The RCVSM and RCVSV can be com- puted by the same set of samples, thus no extra computational cost is introduced with respect to the computations of CVSM and CVSV. From the plots of RCVSM and RCVSV, accurate quantitative information on variance reductions of sample mean and sample variance can be read because of reduced upper bound of the range of the epistemic parameter. For general form of quadratic polynomial output, the analytical solutions of the original and the revised RIMs are given. Numerical example is em- ployed and results demonstrate that the analytical results are consistent and accurate. An engineering example is applied to tes- tify the validity and rationality of the revised RIMs, which can give instructions to the engineers about how to reduce variance of sample mean and sample variance by reducing the range of epistemic parameters.
ISSN:1674-7348
1869-1927
DOI:10.1007/s11433-014-5527-9