Masters Theses
Abstract
“This paper gives a distribution for the ratio of two non-independent normally distributed random variables. The random variables involved are jointly distributed as the bivariate normal with means zero and variance- covariance matrix V.
The sample mean and one-half the sum of the smallest and largest sample observations from the symmetrically truncated Cauchy density function are compared as estimates of the mean of this density function. The reason for this comparison is to determine which of these two estimators gives the best estimate of the mean.
A method to empirically determine the best linear combination of order statistics for any symmetric population to estimate the mean of that population is developed. After the method has been developed, it is applied to the symmetrically truncated Cauchy distribution”--Abstract, page ii.
Advisor(s)
Antle, Charles E.
Committee Member(s)
Miles, Aaron J.
Sauer, Harry J., Jr., 1935-2008
Joiner, James W., 1931-2013
Department(s)
Mathematics and Statistics
Degree Name
M.S. in Applied Mathematics
Publisher
University of Missouri at Rolla
Publication Date
1964
Pagination
iv, 23 pages
Note about bibliography
Includes bibliographical references (page 22).
Rights
© 1964 Robert M. Smith, All rights reserved.
Document Type
Thesis - Open Access
File Type
text
Language
English
Thesis Number
T 1671
Print OCLC #
5963364
Link to Catalog Record
Recommended Citation
Smith, Robert M., "A method to give the best linear combination of order statistics to estimate the mean of any symmetric population" (1964). Masters Theses. 5674.
https://scholarsmine.mst.edu/masters_theses/5674
