I am trying to implement recursive ARIMA that would just update the parameters with new data point, rather than re-estimate them from scratch, without taking into account the previous model. What I have in mind was proposed in:
A. K. Rao, Y. -. Huang and S. Dasgupta, "ARMA parameter estimation using a novel recursive estimation algorithm with selective updating," in IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 38, no. 3, pp. 447-457, March 1990, doi: 10.1109/29.106863
However, I have difficulties finding in the recent papers that anyone is using a similar approach and how is it performed. I would be grateful to hear from someone who might have tried something like that or some reference. With increase of the data by adding new data points, execution of reestimation on the whole set increases. That is the main reason why I would aim for parameters update, rather than reestimation.