Gamma processes

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Authors
Lewis, Peter A. W.
Mckenzie, Edward
Hugus, David Kennedy
Subjects
Beta-Gamma Transformation
Beta-Gamma Process
BGAR(l) Process
Moving Average Processes
Autoregressi ve Process
DBGAR(l) Process
GAR(1) Process
Gamma Innovation
Advisors
Date of Issue
1986-01
Date
1986-01
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
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
Type
Technical Report
Description
Series/Report No
Department
Identifiers
NPS Report Number
NPS55-86-002
Sponsors
Funder
NA
Format
Citation
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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