Numerical Methods for Fitting and Simulating Autoregressive-To-Anything Processes

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. Subject classification: simulation Other Keywords: time series, input modeling, numerical integration Dependent, time-series input processes occur naturally in the simulation of many service, communications and manufacturing systems. For example, the sizes of the demands on an inventory system in successive periods are often dependent because a large demand in one period implies that fewer items will be needed in the following period. Ware, Page and 1 Nelson [13] observed that the times between file accesses on ..