Time Series Forecasting using SARIMAX and compared with ARIMA

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Wonderful and highly resourceful video!! Thanks for this content, I faced same problem of seasonality absence in forecast, this video has explained me to solve this. Keep it coming

totally_insane

p, q, d selection seems arbitrary, could you please explain more? Why is d = 1? The ACF and PACF cross 0 at different points, yet you set both to 2, why? Is log scale and ma deduction the same as differencing the dataset (df.diff(1))?

lajosfidy

Thank you for the video, very nice content, but is sarimax also good for forecasting hourly data?

valdompinga

It is clearly evident in the ACF plot that the seasonality is still present

karteekmenda

arima predicts tranformed stationary data? and how can you see prediction of source data? Yours arima has predicts of ma-data => it is like mean of a chart

dicloniusN

It's a wonderful explanation please could you share the code link or data base .

kumawatgirija

hello can you please feed me with some help, after i fitted the model, when i wanted to predict i had an error that says " Out-of-sample operations in a model with a regression component require additional exogenous values via the `exog` argument" i don't know why this happens

lollmao

Thanks for the great video but I've a doubt like what is Arimax ... Is there any difference in Arimax vs sarimax

mani

Hi TeKnowledGeek, in 10:14 you are saying that the data is sesonal. But you are doing the test_stationarity. Am I wrong or should it say that the data are stationary?

LK-cphw

Further why are you using differencing factor in model d=1 when you have already transferred data into stationary?

TheOraware

so we should take same pdq for sarimax also?

sanjaisrao

how to decide the value of window in

scientensity

Normal order and seasonal order cannot be same there is diffrent way to choose p, d, q and SP, SD, SQ thats why i am here in the video still haven't found the answer . and one more error is you cannot use train test split as it is data at t is dependent on data at t-1. please correct these

kushalmk

I have better error without with non-stationary data))

dicloniusN

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