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NOVÁK, L. NOVÁK, D.
Original Title
On Taylor Series Expansion for Statistical Moments of Functions of Correlated Random Variables dagger
Type
journal article in Web of Science
Language
English
Original Abstract
The paper is focused on Taylor series expansion for statistical analysis of functions of random variables with special attention to correlated input random variables. It is shown that the standard approach leads to significant deviations in estimated variance of non-linear functions. Moreover, input random variables are often correlated in industrial applications; thus, it is crucial to obtain accurate estimations of partial derivatives by a numerical differencing scheme. Therefore, a novel methodology for construction of Taylor series expansion of increasing complexity of differencing schemes is proposed and applied on several analytical examples. The methodology is adapted for engineering applications by proposed asymmetric difference quotients in combination with a specific step-size parameter. It is shown that proposed differencing schemes are suitable for functions of correlated random variables. Finally, the accuracy, efficiency, and limitations of the proposed methodology are discussed.
Keywords
Taylor series expansion; estimation of coefficient of variation; semi-probabilistic approach; structural reliability
Authors
NOVÁK, L.; NOVÁK, D.
Released
31. 8. 2020
Publisher
MDPI
Location
BASEL
ISBN
2073-8994
Periodical
Symmetry
Year of study
12
Number
8
State
Swiss Confederation
Pages from
1
Pages to
14
Pages count
URL
https://www.mdpi.com/2073-8994/12/8/1379
Full text in the Digital Library
http://hdl.handle.net/11012/195719
BibTex
@article{BUT165296, author="Lukáš {Novák} and Drahomír {Novák}", title="On Taylor Series Expansion for Statistical Moments of Functions of Correlated Random Variables dagger", journal="Symmetry", year="2020", volume="12", number="8", pages="1--14", doi="10.3390/sym12081379", issn="2073-8994", url="https://www.mdpi.com/2073-8994/12/8/1379" }