Generation of some first-order autoregressive Markovian sequences of positive random variables with given marginal distributions
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Authors
Lawrance, A. J.
Lewis, P. A. W.
Subjects
Markovian Sequences; Autoregressive; Positive Random Variables; Exponential
processes; NEAR(l) process; Gamma first-order autoregressive process;
Gamma-Beta process; NMEAR(l) process.
Advisors
Date of Issue
1981-03
Date
1981-03
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
Methods for simulating dependent sequences of continuous positive-valued random variables with exponential uniform, Gamma, and mixed exponential marginal distributions are given. In most cases the sequences are first-order, linear autoregressive, Markovian processes. A very broad two-parameter family of this type, GNEAR(1), with exponential marginals and both positive and negative correlation is defined and its transformation to a similar multiplicative process with uniform marginals is given. It is shown that for a subclass of this two-parameter family extension to mixed exponential marginals is possible, giving a model of broad applicability for analyzing data and modelling stochastic systems, although negative correlation is more difficult to obtain than in the exponential case. Finally, two schemes for autoregressive sequences with Gamma distributed marginals are outlined. Efficient simulation of some of these schemes is discussed. (Author)
Type
Technical Report
Description
Series/Report No
Department
Operations Research
Identifiers
NPS Report Number
NPS55-81-003
Sponsors
Naval Postgraduate School, Monterey, CA
Funder
Format
Citation
Distribution Statement
Approved for public release; distribution is unlimited.