Robust empirical Bayes analyses of event rates
Subtitle: Donald P. Gaver, Iognaid G. O'Muircheartaigh
Contributors: O'Muircheartaigh, I. G.; Naval Postgraduate School (U.S.). Dept. of Operations Research
Publisher: Naval Postgraduate School; Available from National Technical Information Service
Published: 1986
Place of publication: Monterey, Calif; Springfield, Va
Language: eng
Number of pages: 53
Subjects: PARAMETRIC ANALYSIS
Other titles: NPS-55-86-007.
Description: A number, I, of nominally similar items generate events (e.g. failures) at possibly different      rates, or mean time intervals. This paper addresses the problem of appropriately pooling the      data from the different sources. The approach is parametric empirical Bayes: true individual      item rates are assumed to come from a fixed superpopulation. It is shown how parameters of      a superpopulation model can be estimated from all of the data, and combined with individual      unit history, can provide improved estimates of individual rates. The procedure can be      robust: evidence that a particular rate is far off from the main body of rates permits that      outlier to stand by itself, i.e. to resist pooling. Illustrative analyses of data are supplied.      Keywords: Robustness; Population(Mathematics); and Charts.
Notes: Cover title.

"NPS-55-86-007."

"March 1986."

AD A166 681.

Includes bibliographical references (p. 35-37).

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