Title :
Model benchmarking with a statistical grading scale
Author :
Weitz, Ronald L. ; Zimmer, William J. ; Calton, Ted L. ; Prairie, Richard R.
Author_Institution :
Sci. Applications Int. Corp., Albuquerque, NM, USA
Abstract :
This paper presents a method for deriving a grading scale for model benchmarking and applies the technique to the benchmarking of the SABER methodology for lethality assessments. The method proposes a grading scale based on the level of acceptance of a goodness-of-fit test. The probability α of rejecting a hypothesis when it is true, as derived from an observed value of a test statistic, is often referred to as the level of acceptance of the test. The hypothesis to be tested here is that the SABER model is valid for a specific application, with α being used as a basis to define various grading levels as an indicator of benchmark success
Keywords :
modelling; probability; simulation; statistical analysis; SABER methodology; benchmark success; goodness-of-fit test; hypothesis rejection; lethality assessments; level of acceptance; model benchmarking; statistical grading scale; test statistic; Benchmark testing; Computational modeling; Computer simulation; Electronic equipment testing; Laboratories; Particle beams; Predictive models; Probability density function; Random variables; Sampling methods;
Conference_Titel :
Reliability and Maintainability Symposium, 1994. Proceedings., Annual
Conference_Location :
Anaheim, CA
Print_ISBN :
0-7803-1786-6
DOI :
10.1109/RAMS.1994.291106