A New Second-Order Autoregressive Time-Series Model in Double Exponential (LAPLACE) Variables -NLAR (2)
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Authors
Dewald, L.S.
Lewis, P.A.W.
Subjects
Time Series
Double Exponential Distribution
Yule-Walker Equations
Residual Analysis
Time Reversibility
Simulation
Autoregressive
Moving Average
Mixed Models
Double Exponential Distribution
Yule-Walker Equations
Residual Analysis
Time Reversibility
Simulation
Autoregressive
Moving Average
Mixed Models
Advisors
Date of Issue
1983-12
Date
December 1983
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
A time-series model for Laplace (double-exponential) variables having second-order autoregressive structure (NLAR(2)) is presented. The model is Markovian and extends the second-order process in exponential variables, NEAR(2), to the case where the marginal distribution is Laplace. The properties of the Laplace distribution make it useful for modeling in some cases where the normal distribution is not appropriate. The time-series model has four parameters and is easily simulated. The autocorrelation function for the process is derived as well as third-order moments to further explore dependency in the process. The model can exhibit a broad range of positive and negative correlations and is partially time reversible.
Type
Technical Report
Description
Series/Report No
Department
Operations Research (OR)
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
NPS55-83-035
Sponsors
Office of Naval Research
Funder
NR-42-284
Format
34 p.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
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.