Numerical methods for fitting and simulating Autoregressive-to-Anything Processes

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.