Relative Entropy Based Method for Probabilistic Sensitivity Analysis in Engineering Design

By Huibin Liu, Wei Chen, Agus Sudjianto. 2006

255 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/c09c34e2511b768751dca3588ce9d039069be0d2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

A simple and efficient method for global sensitivity analysis based on cumulative distribution functions (2015, unknown): “Liu et al. (2006) use the term Regional Response Probabilistic Sensitivity Analysis (RRPSA) to refer to this type of global (or “probabilistic” in their terminology) SA that can focus on specific regions of the response surface.”
A Review on Global Sensitivity Analysis Methods (2014, unknown): “ent importance measures, which do not require any computation of the output moments. Two kinds of indices have been dened: { The entropy-based sensitivity indices (Krzykacz-Hausmann [47], Liu et al. [57], Auder and Iooss [3]), { The distribution based sensitivity indices (Borgonovo [6], Borgonovo et”
Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications (2015, unknown): “Entropy can be regarded as an indicator of the information content or as a measure of the uncertainty of a random variable (Mogheir et al., 2004; Liu et al., 2006; Auder and Iooss, 2009; Mishra et al., 2009).”
Reliability sensitivity analysis for structural systems in interval probability form (2011, background): “For more information, please refer to references (Mundstok and Marczak 2009; Xing et al. 2009; Au 2005; Rahman and Wei 2008; Liu et al. 2006).”
The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020, unknown): “For example, in the context of risk or reliability analysis (Liu et al., 2006), the SA results would be different if the quantity of interest is related to the tail of the distribution of a model output such as a failure probability, a quantile or a super-quantile (Hong and Liu, 2010; Lemaître et…”
Sensitivity analysis of environmental models: A systematic review with practical workflow (2014, methodology): “In this case, even if one were able to derive almost exact estimates of the variance-based sensitivity indices, they would not provide the correct ranking (a numerical example is given in Liu et al. (2006)).”