Exponential Distribution on Test Science Research Document Library https://research.testscience.org/keywords/exponential-distribution/ Recent content in Exponential Distribution on Test Science Research Document Library Hugo -- 0.129.0 en-us Institute for Defense Analyses Mon, 01 Jan 2018 00:00:00 +0000 Parametric Reliability Models Tutorial https://research.testscience.org/post/2018-parametric-reliability-models-tutorial/ Mon, 01 Jan 2018 00:00:00 +0000 https://research.testscience.org/post/2018-parametric-reliability-models-tutorial/ This tutorial demonstrates how to plot reliability functions parametrically in R using the output from any reliability modeling software. It provides code and sample plots of reliability and failure rate functions with confidence intervals for three different skewed probability distributions the exponential, the two-parameter Weibull, and the lognormal. These three distributions are the most common parametric models for reliability or survival analysis. This paper also provides mathematical background for the models and recommendations for when to use them. This tutorial demonstrates how to plot reliability functions parametrically in R using the output from any reliability modeling software. It provides code and sample plots of reliability and failure rate functions with confidence intervals for three different skewed probability distributions the exponential, the two-parameter Weibull, and the lognormal. These three distributions are the most common parametric models for reliability or survival analysis. This paper also provides mathematical background for the models and recommendations for when to use them.

Suggested Citation

Pinelis, Yevgeniya K, and William R Whitledge. “Tutorial: Parametric Reliability Models.” Institute for Defense Analyses IDA Non-Standard Document NS D-9171 (September 2018).

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]]> Statistical Models for Combining Information Stryker Reliability Case Study https://research.testscience.org/post/2015-statistical-models-for-combining-information-stryker-reliability-case-study/ Thu, 01 Jan 2015 00:00:00 +0000 https://research.testscience.org/post/2015-statistical-models-for-combining-information-stryker-reliability-case-study/ Reliability is an essential element in assessing the operational suitability of Department of Defense weapon systems. Reliability takes a prominent role in both the design and analysis of operational tests. In the current era of reduced budgets and increased reliability requirements, it is challenging to verify reliability requirements in a single test. Furthermore, all available data should be considered in order to ensure evaluations provide the most appropriate analysis of the system’s reliability. Reliability is an essential element in assessing the operational suitability of Department of Defense weapon systems. Reliability takes a prominent role in both the design and analysis of operational tests. In the current era of reduced budgets and increased reliability requirements, it is challenging to verify reliability requirements in a single test. Furthermore, all available data should be considered in order to ensure evaluations provide the most appropriate analysis of the system’s reliability. This paper describes the benefits of using parametric statistical models to combine information across multiple testing events. Both frequentist and Bayesian inference techniques are employed and they are compared and contrasted to illustrate different statistical methods for combining information. We apply these methods to data collected during the developmental and operational test phases for the Stryker family of vehicles. We show that, when we combine the available information across two test phases for the Stryker family of vehicles, reliability estimates are more accurate and precise than those reported previously using traditional methods that use only operational test data in their reliability assessments.

Suggested Citation

Steiner, Stefan, Rebecca M. Dickinson, Laura J. Freeman, Bruce A. Simpson, and Alyson G. Wilson. “Statistical Methods for Combining Information: Stryker Family of Vehicles Reliability Case Study.” Journal of Quality Technology 47, no. 4 (October 2015): 400–415. https://doi.org/10.1080/00224065.2015.11918142.

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