Standard Deviation of Logistic Distribution: Theory and Algorithm
by Patrick G. O. Weke and Thomas Achia.
The paper presents a theoretical method based on order statistics
and a FORTRAN program for computing the variance and relative efficiencies
of the standard deviation of the logistic population with respect to the
Cramer-Rao lower variance bound and the best linear unbiased estimators
(BLUE's) when the mean is unknown. A method based on a pair of single
spacing and the 'zero-one' weights rather than the optimum weights are
used. A comparison of an estimator based on four order statistics with the
traditional estimators is considered.
Order Statistics, Logistic Distribution, Parameter Estimation,
Fortran, Relative Efficiencies
JPatrick G. O. Weke, firstname.lastname@example.org
Thomas Achia, email@example.com
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