A new autoregressive time series model in exponential variables (NEAR(1))
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Authors
Lawrance, A. J.
Lewis, P.A.W.
Subjects
Autoregressive model in exponential variables
Negative correlation
Crosscoupled processes
Antithetic variables
Correlated uniform process; Time series
Point process
Simulation.
Negative correlation
Crosscoupled processes
Antithetic variables
Correlated uniform process; Time series
Point process
Simulation.
Advisors
Date of Issue
1980-03
Date
1980-03
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
A new time series model for exponential variables having first order autoregressive structure is presented. Unlike the recently studied standard autoregressive model in exponential variables (EAR(1)), runs of constantly scaled values are avoidable, and the two parameter structure allows some adjustment of time nonreversibility effects in sample path behavior. The model is further developed by the use of cross-coupling and antithetic ideas to allow negative dependency. Joint distributions and autocorrelations are investigated. A transformed version of the model has a uniform marginal distribution and its correlation and regression structures are also obtained. Estimation aspects of the models are briefly considered. (Author)
Type
Technical Report
Description
Series/Report No
Department
Identifiers
NPS Report Number
NPS55-80-011
Sponsors
Naval Postgraduate School, Monterey, CA
Funder
N0001480WR00054
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.