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Richard Hardy
Richard Hardy
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Can multivariate foecasting be done usingthe ARIMA function in statsmodel include covariates?

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Suleka_28
Suleka_28
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I have already implemented a univariate time series forecasting using ARIMA in statsmodel. I know that in R we can put external reggressors using auto ARIMA. Can this be done with statsmodel's ARIMA implementation?

ex: a store has different features like sales, dayOfWeek, promotion and schoolHoliday. I want to use all these features of day d-1 to predict sales of d. Can this be done using the ARIMA implementation of the stats model?

I have already implemented a univariate time series forecasting using ARIMA in statsmodel. I know that in R we can put external reggressors using auto ARIMA. Can this be done with statsmodel's ARIMA implementation?

I have already implemented a univariate time series forecasting using ARIMA in statsmodel. I know that in R we can put external reggressors using auto ARIMA. Can this be done with statsmodel's ARIMA implementation?

ex: a store has different features like sales, dayOfWeek, promotion and schoolHoliday. I want to use all these features of day d-1 to predict sales of d. Can this be done using the ARIMA implementation of the stats model?

added 1 character in body
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Suleka_28
Suleka_28
  • 255
  • 2
  • 8

I have already implemented a univariate time series forecasting using ARIMA in statsmodel. I know that in R we can put external aggressorsreggressors using auto ARIMA. Can this be done with statsmodel's ARIMA implementation?

I have already implemented a univariate time series forecasting using ARIMA in statsmodel. I know that in R we can put external aggressors using auto ARIMA. Can this be done with statsmodel's ARIMA implementation?

I have already implemented a univariate time series forecasting using ARIMA in statsmodel. I know that in R we can put external reggressors using auto ARIMA. Can this be done with statsmodel's ARIMA implementation?

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Suleka_28
Suleka_28
  • 255
  • 2
  • 8