Comparison of the Kalman filter and exponential smoothing techniques of forecasting United States Marine Corps losses in the Republic of Vietnam
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Authors
Allison, William Thomas
Subjects
Advisors
Barrett, E.B.
Date of Issue
1969-10
Date
Publisher
Monterey, California. U.S. Naval Postgraduate School
Language
en_US
Abstract
This paper investigates the application of the Kalman Filter and the
General Exponential Smoothing techniques of forecasting. Both methods
are derived and the similarities and differences between them are discussed.
The two techniques are then applied to the practical problem of
predicting weekly losses suffered by the U. S. Marine Corps units in the
I Corps Tactical Zone in the Republic of Vietnam. The mean absolute
error of the prediction is used as the criterion for choosing the better
of the two methods. Results are given for both techniques as well as
for the method of linear regression. In general the Kalman Filter provides
the smallest mean absolute error for the three mathematical models;
linear, growing sine with harmonics and frequency of sixteen, thirty-two,
and fifty-two weeks, and a constant model.
Type
Thesis
Description
Series/Report No
Department
Operations Research
Organization
Naval Postgraduate School