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Franziska W.
Franziska W.
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I would calculate the daily deltas of your sales data and implement a time series forecast model by using thean Azure ML R or Python/Python model module that predicts the daily deltas until the end of the month and returns the resulting monthly sum.

If you are not familiar with time series analysis, here is a link to a good description of some basic methods and how to apply them using R.

I think, would predict the daily deltas using an ARIMA model. I found this website containing a description of a time series analysis work flow using R with which you could find a good ARIMA model.

I hope, the above is useful for you.

I would calculate the daily deltas of your sales data and implement a time series forecast model using the Azure ML R or Python model module that predicts the daily deltas until the end of the month and returns the resulting monthly sum.

If you are not familiar with time series analysis, here is a link to a good description of some basic methods and how to apply them using R.

I think, would predict the daily deltas using an ARIMA model. I found this website containing a description of a time series analysis work flow using R with which you could find a good ARIMA model.

I hope, the above is useful for you.

I would calculate the daily deltas of your sales data and implement a time series forecast model by using an Azure ML R/Python model module that predicts the daily deltas until the end of the month and returns the resulting monthly sum.

If you are not familiar with time series analysis, here is a link to a good description of some basic methods and how to apply them using R.

I think, would predict the daily deltas using an ARIMA model. I found this website containing a description of a time series analysis work flow using R with which you could find a good ARIMA model.

I hope, the above is useful for you.

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Franziska W.
Franziska W.
  • 311
  • 2
  • 4

I would calculate the daily deltas of your sales data and implement a time series forecast model using the Azure ML R or Python model module that predicts the daily deltadeltas until the end of the month and returns the resulting monthly sum.

If you are not familiar with time series analysis, here is a link to a good description of some basic methods and how to apply them using R. 

I think, would also consider decomposingpredict the daily deltadeltas using an ARIMA model. I found this website containing a description of a time series and to predict only the residual componentanalysis work flow using R with which you could find a good ARIMA model.

I hope, the above is useful for you.

I would calculate the daily deltas of your sales data and implement a time series model using the R or Python model module that predicts the daily delta until the end of the month and returns the resulting monthly sum.

If you are not familiar with time series analysis, here is a link to a good description of some basic methods and how to apply them using R. I would also consider decomposing the daily delta time series and to predict only the residual component.

I hope, the above is useful for you.

I would calculate the daily deltas of your sales data and implement a time series forecast model using the Azure ML R or Python model module that predicts the daily deltas until the end of the month and returns the resulting monthly sum.

If you are not familiar with time series analysis, here is a link to a good description of some basic methods and how to apply them using R. 

I think, would predict the daily deltas using an ARIMA model. I found this website containing a description of a time series analysis work flow using R with which you could find a good ARIMA model.

I hope, the above is useful for you.

Source Link
Franziska W.
Franziska W.
  • 311
  • 2
  • 4

I would calculate the daily deltas of your sales data and implement a time series model using the R or Python model module that predicts the daily delta until the end of the month and returns the resulting monthly sum.

If you are not familiar with time series analysis, here is a link to a good description of some basic methods and how to apply them using R. I would also consider decomposing the daily delta time series and to predict only the residual component.

I hope, the above is useful for you.