Document Type
Report
Source Publication Title
Technical Report 35
Abstract
The theory of structural inference, as developed by Fraser (1968), is based on a group-theoretic approach using invariant Haar measures to Fisher's fiducial theory. Structural inference theory constructs a unique distribution, conditional on the given sample information only, for the parameters of a measurement model. Based on the structural density for the two-parameter lognormal distribution, the structural density and distribution function for the reliability function are derived. Consequently, expressions for structural point and interval estimates of the reliability function are developed. Approximations for large sample sizes and/or moderately reliable components are also discussed. An example based on lognormal data is given to illustrate the theory.
Disciplines
Mathematics | Physical Sciences and Mathematics
Publication Date
12-1-1975
Language
English
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Dyer, Danny D., "Structural Inference on Reliability in a Lognormal Model" (1975). Mathematics Technical Papers. 325.
https://mavmatrix.uta.edu/math_technicalpapers/325