Investigate Threshold AR Models
antoinecarme opened this issue · 7 comments
Introduce some non-linear time series models. Two-regime threshold AR (TAR) models are good candidates.
Original Paper :
Howell Tong
Department of Statistics, The Chinese University of Hong Kong, Shatin, NT, Hong Kong
Tong, H. (1983) Threshold Models in Nonlinear Time Series Analysis. Lecture Notes in Statistics, Springer-Verlag
https://link.springer.com/book/10.1007/978-1-4684-7888-4
https://link.springer.com/chapter/10.1007/978-1-4684-7888-4_3
A good reference is given by :
Nonlinear Time Series Analysis
Author(s):Ruey S. Tay, Rong Chen
https://onlinelibrary.wiley.com/doi/book/10.1002/9781119514312
Avoid reinventing the wheel.
Is there already a decent python implementation ?
Impact on PyAF : TAR and TARX models.
Model Parameters : Delay (d) and Threshold (r)
Explanation : Signal value d=7 days before was above or below threshold r => switch AR models.
The delay d has a functional meaning (business-related, control which AR model to use).
The threshold r can be chosen among signal quantiles (d = q_10, ...., q_90).
PyAF can generate different TAR models (test many values for d and r) simultaneously (parallelization OK).
NTS: An R Package for Nonlinear Time Series Analysis
Published 2020
