Accession Number : ADA293952

Title :   A Dynamic General Linear Model for Inference From Accelerated Life Tests,

Corporate Author : GEORGE WASHINGTON UNIV WASHINGTON DC INST FOR RELIABILITY AND RISK ANALYSIS

Personal Author(s) : Mazzuchi, Thomas A. ; Soyer, Refik

PDF Url : ADA293952

Report Date : 31 AUG 1987

Pagination or Media Count : 20

Abstract : We present a new approach for inference from accelerated life tests. Our approach is based on a dynamic general linear model setup which arises naturally from the accelerated life testing problem and uses linear Bayesian methods for inference. The advantage of the procedure is that it does not require large number of items to be tested and that it can deal with both censored and uncensored data. Furthermore, the approach produces closed form inference results. We illustrate the use of our approach with some actual accelerated life test data. (AN)

Descriptors :   *MATHEMATICAL MODELS, *STATISTICAL INFERENCE, *BAYES THEOREM, LINEAR SYSTEMS, SCENARIOS, WEIBULL DENSITY FUNCTIONS, EXPERIMENTAL DATA, LIFE EXPECTANCY(SERVICE LIFE), TIME DEPENDENCE, RELIABILITY, MATHEMATICAL PREDICTION, EXPONENTIAL FUNCTIONS, LIFE TESTS, ACCELERATED TESTING, DISTRIBUTION FUNCTIONS.

Subject Categories : Statistics and Probability
      Operations Research

Distribution Statement : APPROVED FOR PUBLIC RELEASE