Model Validation on Test Science Research Document Library https://research.testscience.org/keywords/model-validation/ Recent content in Model Validation on Test Science Research Document Library Hugo -- 0.129.0 en-us Institute for Defense Analyses Tue, 01 Jan 2019 00:00:00 +0000 M&S Validation for the Joint Air-to-Ground Missile https://research.testscience.org/post/2019-m-s-validation-for-the-joint-air-to-ground-missile/ Tue, 01 Jan 2019 00:00:00 +0000 https://research.testscience.org/post/2019-m-s-validation-for-the-joint-air-to-ground-missile/ An operational test is resource-limited and must therefore rely on both live test data and modeling and simulation (M&S) data to inform a full evaluation. For the Joint Air-to-Ground Missile (JAGM) system, we needed to create a test design that accomplished dual goals, characterizing missile performance across the operational space and supporting rigorous validation of the M&S. Our key question is which statistical techniques should be used to compare the M&S to the live data? An operational test is resource-limited and must therefore rely on both live test data and modeling and simulation (M&S) data to inform a full evaluation. For the Joint Air-to-Ground Missile (JAGM) system, we needed to create a test design that accomplished dual goals, characterizing missile performance across the operational space and supporting rigorous validation of the M&S. Our key question is which statistical techniques should be used to compare the M&S to the live data?

Suggested Citation

Crabtree, Brent, Andrew Cseko, Joel Williamson, and Kelly Avery. M&S Validation for the Joint Air-to-Ground Missile. Alexandria, VA: Institute for Defense Analyses, 2019.

Poster:

]]> Validating the PRA Testbed Using a Statistically Rigorous Approach https://research.testscience.org/post/2015-validating-the-pra-testbed-using-a-statistically-rigorous-approach/ Thu, 01 Jan 2015 00:00:00 +0000 https://research.testscience.org/post/2015-validating-the-pra-testbed-using-a-statistically-rigorous-approach/ For many systems, testing is expensive and only a few live test events are conducted. When this occurs, testers frequently use a model to extend the test results. However, testers must validate the model to show that it is an accurate representation of the real world from the perspective of the intended uses of the model. This raises a problem when only a small number of live test events are conducted, only limited data are available to validate the model, and some testers struggle with model validation. For many systems, testing is expensive and only a few live test events are conducted. When this occurs, testers frequently use a model to extend the test results. However, testers must validate the model to show that it is an accurate representation of the real world from the perspective of the intended uses of the model. This raises a problem when only a small number of live test events are conducted, only limited data are available to validate the model, and some testers struggle with model validation. This article describes a statistically rigorous approach for validating a model with only a small number of live test results. We discuss a specific application for validating a model of a naval surface combatant defending itself against a cruise missile attack. The approach takes into account potential correlation in the data and other factors that may drive system performance.

Suggested Citation

Thomas, Dean, and Rebecca Dickinson. “Validating the Probability of Raid Annihilation Testbed Using a Statistical Approach.” The ITEA Journal of Test and Evaluation 36, no. 2 (June 2015).

Paper:

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