Numerical methods for fitting and simulating autoregressive-to-anything processes

Marne C. Cario; Barry L. Nelson

doi:10.1287/ijoc.10.1.72

Numerical methods for fitting and simulating autoregressive-to-anything processes

Marne C. Cario^*, Barry L. Nelson

^*Corresponding author for this work

Industrial Engineering and Management Sciences

Research output: Contribution to journal › Article › peer-review

67 Scopus citations

Abstract

An ARTA (AutoRegressive-to-Anything) Process is a time series with arbitrary marginal distribution and autocorrelation structure specified through finite lag p. We develop an efficient numerical method for fitting ARTA processes and discuss its implementation in the software ARTAFACTS. We also present the software ARTAGEN that generates observations from ARTA processes for use as inputs to a computer simulation. We illustrate the use of the software with a real-world example.

Original language	English (US)
Pages (from-to)	72-81
Number of pages	10
Journal	INFORMS Journal on Computing
Volume	10
Issue number	1
DOIs	https://doi.org/10.1287/ijoc.10.1.72
State	Published - 1998

Keywords

Input modeling
Time series

ASJC Scopus subject areas

Software
Information Systems
Computer Science Applications
Management Science and Operations Research

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10.1287/ijoc.10.1.72

Cite this

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abstract = "An ARTA (AutoRegressive-to-Anything) Process is a time series with arbitrary marginal distribution and autocorrelation structure specified through finite lag p. We develop an efficient numerical method for fitting ARTA processes and discuss its implementation in the software ARTAFACTS. We also present the software ARTAGEN that generates observations from ARTA processes for use as inputs to a computer simulation. We illustrate the use of the software with a real-world example.",

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AB - An ARTA (AutoRegressive-to-Anything) Process is a time series with arbitrary marginal distribution and autocorrelation structure specified through finite lag p. We develop an efficient numerical method for fitting ARTA processes and discuss its implementation in the software ARTAFACTS. We also present the software ARTAGEN that generates observations from ARTA processes for use as inputs to a computer simulation. We illustrate the use of the software with a real-world example.

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KW - Time series

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Numerical methods for fitting and simulating autoregressive-to-anything processes

Abstract

Keywords

ASJC Scopus subject areas

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