An analysis of sensitivity tests

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A new method of analyzing sensitivity tests is proposed. It uses the Likelihood Ratio Test to compute regions of arbitrary confidence. It can calculate confidence regions for the parameters of the distribution (e.g., the mean, {mu}, and the standard deviation, {sigma}) as well as various percentiles. Unlike presently used methods, such as those based on asymptotic analysis, it can analyze the results of all sensitivity tests, and it does not significantly underestimate the size of the confidence regions. The main disadvantage of this method is that it requires much more computation to calculate the confidence regions. However, these calculations can … continued below

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24 pages

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Neyer, Barry T. March 6, 1992.

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Description

A new method of analyzing sensitivity tests is proposed. It uses the Likelihood Ratio Test to compute regions of arbitrary confidence. It can calculate confidence regions for the parameters of the distribution (e.g., the mean, {mu}, and the standard deviation, {sigma}) as well as various percentiles. Unlike presently used methods, such as those based on asymptotic analysis, it can analyze the results of all sensitivity tests, and it does not significantly underestimate the size of the confidence regions. The main disadvantage of this method is that it requires much more computation to calculate the confidence regions. However, these calculations can be easily and quickly performed on most computers.

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24 pages

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OSTI; NTIS; GPO Dep.

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  • Other: DE92010353
  • Report No.: MLM-3736
  • Grant Number: AC04-88DP43495
  • Office of Scientific & Technical Information Report Number: 5654343
  • Archival Resource Key: ark:/67531/metadc1086647

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Office of Scientific & Technical Information Technical Reports

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  • March 6, 1992

Added to The UNT Digital Library

  • Feb. 10, 2018, 10:06 p.m.

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  • May 16, 2019, 12:47 p.m.

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Neyer, Barry T. An analysis of sensitivity tests, report, March 6, 1992; United States. (https://digital.library.unt.edu/ark:/67531/metadc1086647/: accessed June 10, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT Libraries Government Documents Department.

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