Data Scientist with excellent R skills to write loop fitting auto arima

Job Description:

I am trying to apply auto arima to partitions/windows within my dataset and I haven't the slightest clue on how to even begin. I need to join 6 separate columns back to my original data frame (revenue prep, confidence intervals 95).

1.) I want to train a separate model on each partner_id using the rows c_id = "none" and then forecast/predict values out to the max(date) for each partner_id. The number of months/rows for each partner vary in length. For this example data frame pasted below, partner_id = "1A9" has 12 months/rows with c_id = "none" vs partner_id = "1B9" has 13 months/row with c_id = "none". The number of months/rows extended out to the max(Date) within each partner_id varies as well. Again, auto arima needs to be trained on the c_id = "none" rows and then forecasted for every month until the next partition or partner_id begins.

example: in the df provided, auto arima should be trained on all rows where c_id = 'none' and then forecasted remaining months for partner_id = '1A9'. Forecast revenue and 95 confidence intervals should be returned

2.) the next forecast should be trained on the c_id != "none" within the partner_id partition and and forecasted when the c_id rows change to a different value.

example: in the df provided, auto arima should be trained on all rows where c_id = 'c-100' and then forecasted on c_id == 'c-101' for partner_id == '1A9'. Forecast revenue and 95 prediction intervals should be returned as well.

NOTE: Not all partner_id's will have data for the second forecast values so those rows should just return null if another c_id doesn't exist within the partition

Taidot: R-ohjelmointikieli, Tilastotiede, Datatiede

Tietoa asiakkaasta:
( 0 arvostelua ) San Carlos, United States

Projektin tunnus: #28205617

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