Is TRAMO-SEATS automatic identification of Reg-ARIMA ... - Cemfi

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Results: For the 25000 series with 120,2/3 of the time correct identification of full model. Id with 240,4/5 of the time. Correct identification of the differencing- 120 94%- 240 97%Most failures due to:- Detecting stationary seasonality.- Large real AR roots.Table 5:Errors in Airline model detection (in % of series in group)120 240Airline model 21.9 14.3Other seasonal 15.6 6.3Non-seasonal 0.2 0.1Total 12.8 7.0 No over-detection of Airline models.(Rather the opposite!)23
Table 6:Errors in differencing polynomials (in % of series in group)Regulardifferences DSimulated modelSeasonaldifferences BD0 01 02 00 11 12 1# of obs.in series# of series ingroupErrors in DErrors in BDUnder-diff. Over-diff. Under-diff. Over-diff.Total errors indiff. polynomial120 4500 --- 8.3 --- 4.0 10.7240 4500 --- 7.1 --- 1.4 7.8120 4250 0.0 1.6 --- 0.8 2.4240 4250 0.0 0.7 --- 0.2 0.8120 1000 12.5 --- --- 0.3 12.6240 1000 1.8 --- --- 0.4 2.2120 1500 --- 7.0 2.0 --- 9.0240 1500 --- 3.7 0.3 --- 3.9120 13500 3.7 0.4 1.0 --- 4.8240 13500 0.7 0.3 0.1 --- 1.2120 250 9.2 --- 1.6 --- 10.8240 250 1.2 --- 0.0 --- 1.2Total (*) 120 25000 2.6 2.4 0.6 0.9 6.1240 25000 0.5 1.8 0.1 0.3 2.5(*) in % of relevant groups24
Page 1 and 2: April 2012Is TRAMO-SEATS automatici
Page 3 and 4: TRAMO, SEATS and TSWvsTRAMO+, SEATS
Page 5 and 6: (2) Components in STSM approach: al
Page 7 and 8: Because all users need not be model
Page 9 and 10: Important model:Seasonal series:Air
Page 11 and 12: Series simulated from n.i.i.d. (0,1
Page 13 and 14: B. NON-SEASONAL MODELS (8000 series
Page 15 and 16: C. OTHER SEASONAL MODELS (8500 seri
Page 17 and 18: The complete set contains many mode
Page 19 and 20: Table 1:Errors in Log/Level test (i
Page 21 and 22: Pre-test and final detection of sea
Page 23: Table 4:ARIMA model correct identif
Page 27 and 28: Table 8:Simulated series: model dia
Page 29 and 30: ONE WORD OF CAUTION:TRAMO-SEATS and
Page 31 and 32: SIMULATED SERIESIn summary, If seri
Page 33 and 34: Table 11: GeneralGroup# observ-Aver
Page 35 and 36: Table 12: OutliersGroup (by NZ)% of
Page 37 and 38: Table 15: Detection of seasonalityG
Page 39 and 40: ARIMA MODEL IDENTIFICATIONTable 16:
Page 41 and 42: Table 18:Real series: Model diagnos
Page 43 and 44: Model diagnostics All tests carried
Page 45 and 46: Out-of-sample forecast tests:- F-te
Page 47 and 48: %4846444240383634323028262422201816
Page 49 and 50: %2827262524232221201918171615141312
Page 51 and 52: Comparing the results for the simul
Page 53 and 54: Table 21: Features of decomposition
Page 55 and 56: Table 22:Decomposition failures (1)
Page 57: Back to original question: For seri

Is TRAMO-SEATS automatic identification of Reg-ARIMA ... - Cemfi

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