Gamma processes
By: P.A.W. Lewis, E. Mckenzie, D.K. Hugus
Contributors: Mckenzie, Edward; Hugus, David Kennedy; 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: 35
Subjects: REGRESSION ANALYSIS; MAXIMUM LIKELIHOOD ESTIMATION
Other titles: NPS-55-86-002.
Description: The Beta Gamma transformation is described and is used to define a very simple first order      autoregressive Beta Gamma process, BGAR(1). Maximum likelihood estimation is discussed      for this model, as well as moment estimators. The first-order structure is extended to include      moving average processes and mixed first-order autoregressive, pth-order moving average      processes. It is shown that these Gamma processes are time-reversible and, therefore, too      narrow for general physical modelling. A dual process to the BGAR(1) process, DBGAR(1),      is introduced, as well as an iterated process which combines the Beta-Gamma process and      the GAR(1) process of Gaver and Lewis (1980). Some properties of these extended      autoregressive processes are derived. Several highly nonlinear extensions of these processes      which produce negative correlation are given. Keywords: Beta Gamma Transformation; Beta      Gamma Process, Moving Average Processes; Autoregressive Process; Gamma Innovation.
Notes: Title from cover.

"NPS-55-86-002."

"January 1986."

AD A165 390.

Includes bibliographical references (p. 33-34).

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