Nearly Best Conditional Linear Unbiased Estimation of the Mean and Standard Deviation of the Logistic Distribution.
Abstract
The method of Lagrangian multipliers is used to find nearly best, minimum-variance, linear, unbiased, conditional estimator coefficients for the mean and standard deviation of the logistic distribution using M-order statistics. Coefficients for conditional parameter estimation are developed for full and censored samples of size N = 2(1)40. The equations for the estimators are derived in detail. Two types of censoring are used; single censoring from above and symmetrical censoring from each end. The results are presented in tables of coefficients for conditional estimation of the unknown parameter. It is shown how the tabled coefficients can be used for simultaneous estimation. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1969
- Accession Number
- AD0768718
Entities
People
- Stephen A. Hunter
Organizations
- Air Force Institute of Technology