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Feb 19th, 2018
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  1. fit <-auto.arima(y,xreg=x,seasonal=c(0,1,1)[4])
  2. summary(fit)
  3.  
  4. seasonal=c(0,1,1)[4]
  5.  
  6. qtrs y x
  7. 1Q14 41.7 16963482
  8. 2Q14 26 8857757
  9. 3Q14 22.4 6308120
  10. 4Q14 17.6 4872037
  11. 1Q15 47.7 20304915
  12. 2Q15 30.7 8800350
  13. 3Q15 25.6 8065914
  14. 4Q15 17.4 8.41E+06
  15. 1Q16 59.4 39076150
  16. 2Q16 35.6 23348752
  17. 3Q16 33.5 26721456
  18. 4Q16 23.9 17934787
  19. 1Q17 81.7 65821538
  20. 2Q17 44.8 35845803
  21. 3Q17 42.1 34753415
  22. 4Q17 28.5 21449909
  23. 1Q18 90 84207978
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