The Use of the Empirical Probability Generating Function to Estimate the Neyman Type A Distribution Parameters
useofempiricalpr00bish.pdf (4.194Mb)Abstract
The Maximum Likelihood estimators for the Neyman Type A distribution parameters are very difficult to compute. In this thesis, the Empirical Probability Generating Function is used to provide estimators that are easier to compute and have asymptotic efficiency at least as high as 97% of that for the Maximum Likelihood estimators over most of the parameter space considered. The estimators found by this method are consistently better than the Method of Moments and the Method of Zero Frequency estimators with respect to asymptotic efficiency. The considerations of preference in using one method over another are discussed.
Collections
Related items
Showing items related by title, author, creator and subject.
-
Empirical Bayes risk evaluation with type II censored data
(Monterey, California. Naval Postgraduate School, 1991-07); NPS-OR-91-21Empirical Bayes estimators for the scale parameter in a Weibull, Raleigh or an exponential distribution with type II censored data are developed. These estimators are derived by the matching moment method, the maximum ... -
Stationary discrete autoregressive-moving average time series generated by mixtures
(Monterey, California. Naval Postgraduate School, 1982-01); NPS-55-82-003Two simple stationary processes of discrete random variables with arbitrarily chosen first-order marginal distributions, DARMA(p,N+1) and NDARMA(p,N), are given. The correlation structure of these processes mimics that of ... -
Regression models of quarterly overhead costs for six government aerospace contractors.
(1986-03);Since overhead costs constitute a large percentage of total cost for aerospace contractors, it is important to be able to predict them accurately. The research performed in this thesis takes six government aerospace ...
