[Feature Request]: ARFIMA

[TarandeepKang]

Description

No response

Purpose

Enhancement to time series models

Use-case

Useful with long memory processes whose autocorrelation functions decay more slowly than short memory processes typically used in ordinary ARIMA

Is your feature request related to a problem?

Current implementation unsuitable for long memory processes

Is your feature request related to a JASP module?

Time Series

Describe the solution you would like

No response

Describe alternatives that you have considered

No response

Additional context

Without looking in a textbook, and using only the stuff that is already in my reference manager,, these should give an illustration of the method, it is implemented in the fracdiff package.

Haslett, J., & Raftery, A. E. (1989). Space-Time Modelling with Long-Memory Dependence: Assessing Ireland’s Wind Power Resource. Journal of the Royal Statistical Society. Series C (Applied Statistics), 38(1), 1–50. https://doi.org/10.2307/2347679
Jensen, A. N., & Nielsen, M. Ø. (2014). A Fast Fractional Difference Algorithm. Journal of Time Series Analysis, 35(5), 428–436. https://doi.org/10.1111/jtsa.12074
Peiris, M. S., & Perera, B. J. C. (1988). On Prediction with Fractionally Differenced Arima Models. Journal of Time Series Analysis, 9(3), 215–220. https://doi.org/10.1111/j.1467-9892.1988.tb00465.x
Reisen, V. A., & Lopes, S. (1999). Some simulations and applications of forecasting long-memory time-series models. Journal of Statistical Planning and Inference, 80(1), 269–287. https://doi.org/10.1016/S0378-3758(98)00254-7

[TarandeepKang]

Apologies, but it occurs to me that you might already be using the forecast package for time series functionality. In which case I suppose this would be preferable: https://www.rdocumentation.org/packages/forecast/versions/8.23.0/topics/arfima