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Estimation of conditional moment by moving least squares and its application for importance analysis

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  • Wenbin Ruan
  • Zhenzhou Lu
  • Pengfei Wei

Abstract

Combined with advantages of moving least squares approximation, a new method for estimating higher-order conditional moment is established, which is useful for application in importance analysis and provides a supplement of the standard variance-based importance analysis. On the other hand, after obtaining the first four-order moments, the probability density function can be emulated by use of the Edgeworth expansion procedure, thereby a new method to compute the moment independent importance measure index δ i proposed by Borgonovo is presented in this article. Two examples are employed to demonstrate that it is necessary to analyze higher-order conditional moment in importance analysis. At the same time, we study the feasibility of the Edgeworth expansion-based method for estimating the index δ i by applying it to these examples.

Suggested Citation

  • Wenbin Ruan & Zhenzhou Lu & Pengfei Wei, 2013. "Estimation of conditional moment by moving least squares and its application for importance analysis," Journal of Risk and Reliability, , vol. 227(6), pages 641-650, December.
    • Handle: RePEc:sae:risrel:v:227:y:2013:i:6:p:641-650
    DOI: 10.1177/1748006X13493241
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    References listed on IDEAS

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