Mixed two-stage derivative estimator for sensitivity analysis

نویسندگان

  • Kolsoom Mirabi Department of Statistics, School of Mathematical Sciences, Shahrood University of Technology, Shahrood, Iran
  • Mohammad Arashi Department of Statistics, School of Mathematical Sciences, Shahrood University of Technology, Shahrood, Iran
چکیده مقاله:

In mathematical modeling, determining most influential parameters on outputs is of major importance. Thus, sensitivity analysis of parameters plays an important role in model validation. We give detailed procedure of constructing a new derivative estimator for general performance measure in Gaussian systems. We will take advantage of using score function and measure-value derivative estimators in our approach. It is shown that the proposed estimator performs better than other estimators for a dense class of test functions in the sense of having smaller variance.

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عنوان ژورنال

دوره 5  شماره 1

صفحات  41- 52

تاریخ انتشار 2017-06-01

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