Forecasting Future Sales Using ARIMA and SARIMAX

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[priyaarora]

Every body is using very easy to see "seasonal" dtaa to make youtube videos. If you wanna teach, teach with a highly random data!!!

[arjyabasu]

Pretty complex topic sir...need an intuition video of this !!

[ashishmishra]

Most most awaited video for me, Thanks a lot sir 🙏🙏🙏🙏

[thangasamyp]

Super explanation sir. I have thanks to you for my doubts clear from this lecture. Thank you sir.

[Punkorealist]

Hello, I was wondering if there is a reason why I am getting NaNs when fitting the sarimax model? I have gotten my p =1, d= 1, and q =1, but I dont know why I am getting Nans after doing the fitting. any help would be vauable. Thanks!

[naharaldamer]

thank you, I have one question, what is the purpose of converting data to stationary if you will going to use non-stationary data to fit the model and do the prediction?

[riyasmohammad]

I read an article about sarimax and was really confused. But this video helped me to understand easily.
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[alanpalacios]

I never understood this at college and now it is really clear with your example. Thanks a lot!

[abhisheksharma]

first differencing (of order=1) has been done to de-trend the data. Once it is de-trended, it should further be deseasonalised by differencing again (of order =12). Thus, we have original data-> order1 differencing -> order 12 differencing. The final data will now start from t=14, and it is then checked for stationarity by ADF. The values of PACF at lag=1, lag=12 (for the final transformed data, after two levels of differences) are comparatively higher than PACF values at other lags (as evident from figures). Thus p has been taken as 1, implying AR(1). actually it is written as 1, 1, 1, 12. p is taken as 1, because it reflects the highest PACF value, means 1 lagged value is highly correlated with its subsequent value as compared to other lag values.

[dramekandya]

Very good teacher, his explication is clear and efficient thank your very much

[ruvitkon]

Thank you very much. This really helped me on completing my final year project :)

[aibits]

i have used caltrans dataset (5 min interval data for 6 month) for training and testing and this data have seasonality but it does not have trend, so i have used SARIMA model. but this model fails to forcast. any help would be appreciated.

[zollen]

Is it possible to input multiple time series data (vector autoregression) to these ARIMAX and SARIMAX models?

[nishantjindal]

Hey Krish QQ for forecasting which is better Arima/Sarima or RNN is there any comparison?

[nikhilvishnuvadlamudi]

at 10:05 - You mentioned that we will accept the null hypothesis. There is correction here - you never accept the null hypothesis, its just that there isn't enough evidence to reject it.

[technospider]

Hey! Krish can you suggest to me which model gives me better accuracy if I have only a 15min dataset (performing time-series dataset).. plz I am waiting for your answer.

[ravibengeri]

Hi Sir, What approach we should follow when the target variable is following sigmoid or logistic or S curve with respect to time.
Shall we still apply Time Series? If we can which algorithm we should chose as it has multiple variables affecting target variable?

[ssvipl]

Hi Krish, Good coverage of the ARIMA workflow. If the screen is zoomed, it would have been more easy for the visibility of the code.

[Irhtayagradnus]

Hi, How will you process this model with user input like if user give, year = 2000 then this has to feed to the algorithm dynamically and then forecasting needs to happen . how can we do that?

[galymzhankenesbekov]

I have faced the problem of scientific notation in y-axis, how can i convert it to normal one? i am using df.groupby ....sum().plot(), where can i use .format()? thanks