http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Accelerated life testing of one-shot devices
1 online resource (xiii, 223 pages) : illustrations
"A one-shot device is a unit that performs its function only once and cannot be used for testing more than once. Examples include electric explosive devices, fire extinguishers, airbags in cars, and missiles. While testing one-shot devices, only the condition of the device at a specific inspection time can be recorded, and exact failure times cannot be obtained from the test. As a result, the lifetimes of devices are either left- or right-censored. Due to a lack of lifetime data collected in life-tests, estimating the reliability of one-shot devices in traditional approaches becomes challenging. This book primarily focuses on fundamental issues of statistical modeling based on one-shot device testing data collected from accelerated life-tests. This book also provides advanced statistical techniques. For instance, expectation-maximization algorithms and Bayesian approaches to deal with the estimation challenges, along with comprehensive data analysis of one-shot devices under accelerated life-tests. Readers may apply the techniques from this book to their own lifetime data with censoring. This book is ideal for graduate students, researchers, and engineers working on accelerated life testing data analysis"--
Front Matter -- One-Shot Device Testing Data -- Likelihood Inference -- Bayesian Inference -- Model Mis-Specification Analysis and Model Selection -- Robust Inference -- Semi-Parametric Models and Inference -- Optimal Design of Tests -- Design of Simple Step-Stress Accelerated Life-Tests -- Competing-Risks Models -- One-Shot Devices with Dependent Components -- Conclusions and Future Directions -- Derivation of Hi(a, b) -- Observed Information Matrix -- Non-Identifiable Parameters for SSALTs Under Weibull Distribution -- Optimal Design Under Weibull Distributions with Fixed w1 -- Conditional Expectations for Competing Risks Model Under Exponential Distribution -- Kendall's Tau for Frank Copula.
Narayanaswamy Balakrishnan, McMaster University, Hamilton, Canada, Man Ho Ling, the Education University of Hong Kong, Tai Po, Hong Kong, Hon Yiu So, University of Waterloo, Waterloo, Canada.
Includes bibliographical references and indexes.