I have a minutely dataset for a year duration. It has a daily seasonality. This would imply a seasonal period of 1440 according to https://robjhyndman.com/hyndsight/seasonal-periods/ .
I thought of using the SARIMA (𝑝,𝑑,𝑞)×(𝑃,𝐷,𝑄)𝑠 model with the following parameters : order : (𝑝,𝑑,𝑞) - (6,0,0) - ACF and PACF hinted at a pure AR process
I have trouble determining the (𝑃,𝐷,𝑄).
𝑠 - 1440
However even for (𝑃,𝐷,𝑄) = (1,0,0), the model.fit takes a really long time.
train size - 216,000 data points.
I suspect it is due to the high 's' value.
Is SARIMA not meant to handle minute level data with daily seasonality?