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    <title>Department of Defense on Test Science Research Document Library</title>
    <link>https://research.testscience.org/keywords/department-of-defense/</link>
    <description>Recent content in Department of Defense on Test Science Research Document Library</description>
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    <copyright>Institute for Defense Analyses</copyright>
    <lastBuildDate>Wed, 01 Jan 2020 00:00:00 +0000</lastBuildDate>
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      <title>Circular Prediction Regions for Miss Distance Models under Heteroskedasticity</title>
      <link>https://research.testscience.org/post/2020-circular-prediction-regions-for-miss-distance-models-under-heteroskedasticity/</link>
      <pubDate>Wed, 01 Jan 2020 00:00:00 +0000</pubDate>
      <guid>https://research.testscience.org/post/2020-circular-prediction-regions-for-miss-distance-models-under-heteroskedasticity/</guid>
      <description>Circular prediction regions are used in ballistic testing to express the uncertainty in shot accuracy. We compare two modeling approaches for estimating circular prediction regions for the miss distance of a ballistic projectile. The miss distance response variable is bivariate normal and has a mean and variance that can change with one or more experimental factors. The first approach fits a heteroskedastic linear model using restricted maximum likelihood, and uses the Kenward-Roger statistic to estimate circular prediction regions.</description>
      <content:encoded><![CDATA[<p>Circular prediction regions are used in ballistic testing to express the uncertainty in shot accuracy. We compare two modeling approaches for estimating circular prediction regions for the miss distance of a ballistic projectile. The miss distance response variable is bivariate normal and has a mean and variance that can change with one or more experimental factors. The first approach fits a heteroskedastic linear model using restricted maximum likelihood, and uses the Kenward-Roger statistic to estimate circular prediction regions. The second approach fits the analogous Bayesian model with unrestricted likelihood modifications, and computes circular prediction regions by sampling from the posterior predictive distribution. The two approaches are applied to an example problem, and are compared using simulation.</p>
<h4 id="suggested-citation">Suggested Citation</h4>
<blockquote>
<p>Johnson, Thomas H., John T. Haman, Heather Wojton, and Laura Freeman. “Circular Prediction Regions for Miss Distance Models under Heteroskedasticity.” Quality and Reliability Engineering International 37, no. 7 (November 2021): 2991–3003. <a href="https://doi.org/10.1002/qre.2771">https://doi.org/10.1002/qre.2771</a>.</p>
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    <item>
      <title>DOT&amp;E Reliability Course</title>
      <link>https://research.testscience.org/post/2016-dot-e-reliability-course/</link>
      <pubDate>Fri, 01 Jan 2016 00:00:00 +0000</pubDate>
      <guid>https://research.testscience.org/post/2016-dot-e-reliability-course/</guid>
      <description>This reliability course provides information to assist DOT&amp;amp;E action officers in their review and assessment of system reliability. Course briefings cover reliability planning and analysis activities that span the acquisition life cycle. Each briefing discusses review criteria relevant to DOT&amp;amp;E action officers based on DoD policies and lessons learned from previous oversight efforts.
Suggested Citation Avery, Matthew, Jonathan Bell, Rebecca Medlin, and Freeman Laura. DOT&amp;amp;E Reliability Course. IDA Document NS D-5836.</description>
      <content:encoded><![CDATA[<p>This reliability course provides information to assist DOT&amp;E action officers in their review and assessment of system reliability. Course briefings cover reliability planning and analysis activities that span the acquisition life cycle. Each briefing discusses review criteria relevant to DOT&amp;E action officers based on DoD policies and lessons learned from previous oversight efforts.</p>
<h4 id="suggested-citation">Suggested Citation</h4>
<blockquote>
<p>Avery, Matthew, Jonathan Bell, Rebecca Medlin, and Freeman Laura. DOT&amp;E Reliability Course. IDA Document NS D-5836. Alexandria, VA: Institute for Defense Analyses, 2016.</p>
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      <title>A Comparison of Ballistic Resistance Testing Techniques in the Department of Defense</title>
      <link>https://research.testscience.org/post/2014-a-comparison-of-ballistic-resistance-testing-techniques-in-the-department-of-defense/</link>
      <pubDate>Wed, 01 Jan 2014 00:00:00 +0000</pubDate>
      <guid>https://research.testscience.org/post/2014-a-comparison-of-ballistic-resistance-testing-techniques-in-the-department-of-defense/</guid>
      <description>This paper summarizes sensitivity test methods commonly employed in the Department of Defense. A comparison study shows that modern methods such as Neyer&amp;rsquo;s method and Three-Phase Optimal Design are improvements over historical methods.
Suggested Citation Johnson, Thomas H., Laura Freeman, Janice Hester, and Jonathan L. Bell. “A Comparison of Ballistic Resistance Testing Techniques in the Department of Defense.” IEEE Access 2 (2014): 1442–55. https://doi.org/10.1109/ACCESS.2014.2377633.
Paper: </description>
      <content:encoded><![CDATA[<p>This paper summarizes sensitivity test methods commonly employed in the Department of Defense. A comparison study shows that modern methods such as Neyer&rsquo;s method and Three-Phase Optimal Design are improvements over historical methods.</p>
<h4 id="suggested-citation">Suggested Citation</h4>
<blockquote>
<p>Johnson, Thomas H., Laura Freeman, Janice Hester, and Jonathan L. Bell. “A Comparison of Ballistic Resistance Testing Techniques in the Department of Defense.” IEEE Access 2 (2014): 1442–55. <a href="https://doi.org/10.1109/ACCESS.2014.2377633">https://doi.org/10.1109/ACCESS.2014.2377633</a>.</p>
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