Accession Number : AD0768718
Title : Nearly Best Conditional Linear Unbiased Estimation of the Mean and Standard Deviation of the Logistic Distribution.
Descriptive Note : Master's thesis,
Corporate Author : AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OHIO SCHOOL OF ENGINEERING
Personal Author(s) : Hunter,Stephen A.
Report Date : DEC 1969
Pagination or Media Count : 293
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)
Descriptors : (*SAMPLING, *STATISTICAL DISTRIBUTIONS), ANALYSIS OF VARIANCE, APPROXIMATION(MATHEMATICS), PROBABILITY DENSITY FUNCTIONS, MATRICES(MATHEMATICS), TABLES(DATA), THESES
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE