Output - Aster Analytics

Teradata Aster® Analytics Foundation User GuideUpdate 2
Product
Aster Analytics
Release Number
7.00.02
Published
September 2017
Language
English (United States)
Last Update
2018-04-17
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uce1497542673292.ditamap
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AA-notempfilter_pdf_output.ditaval
dita:id
B700-1022
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Product Category
Software
VARMAX Example 3 Output Table (Columns 1-4)
id coef coef_value stepahead
1 coef 1, 1, 1, 1, 0, 0, 0  
1 ar_params [[1.2280127869768733, 0.10369097626637279, 0.7141124344630049], [1.6892503311514915, -0.7866365569885521, 1.2398648486516826], [2.5905232539842906, -1.9806470096597304, 0.848961995714201]]  
1 ma_params [[-1.3578087849315306, 3.1929513989417986, -0.507843441200345], [-0.27161298036695314, 2.0434556838776285, -0.6532994061098848], [-0.3314681626075737, 0.9709146220990982, 0.4986214533613408]]  
1 exogenous_params    
1 seasonal_ar_params [[-0.8516241752486389, 1.4543285878588237, -1.717424059774754], [0.27802014575224626, 1.1028023698734997, -1.981710680445198], [3.6436081834691665, -0.6515504279942187, 0.2101671051863758]]  
1 seasonal_ma_params    
1 period 4  
1 lag 0  
1 sigma [[8687.149620951508, 7948.571854972013, 2273.0461867165814], [7948.571854972013, 12790.637540035925, 1116.4386244141892], [2273.0461867165814, 1116.4386244141892, 3484.41990598517]]  
1 aic 26.97888751820004  
1 bic 28.130584042443644  
1 iterations 60  
1 converged true  
1     1
1     2
1     3
2 coef 1, 1, 1, 1, 0, 0, 0  
2 ar_params [[-2.8588217461202174, 2.132413356693889, 0.048031825091634464], [-1.6669033637617956, 1.0810782826131897, 0.2430782867637148], [-0.4730750055653358, 0.024891878448287257, 0.2376339870230307]]  
2 ma_params [[1.7104434579564591, -2.139631490133681, -0.4000963233539877], [2.995949635314298, -2.2697549832800177, -2.5616082579956614], [0.30188472672917305, -0.7646261744793058, -0.21255497859171532]]  
2 exogenous_params    
2 seasonal_ar_params [[-2.8260118262809155, 2.7154238951166594, -0.8509533086123783], [-2.9395646286325388, 3.1247969541738883, -1.7883773157208929], [-1.3822487137932813, 1.1513048428957071, 0.29884692571288657]]  
2 seasonal_ma_params    
2 period 4  
2 lag 0  
2 sigma [[8931.17883016103, 9690.562795737687, 4251.384014300442], [9690.562795737687, 17621.68165475026, 4888.406402279781], [4251.384014300442, 4888.406402279781, 3825.021513435783]]  
2 aic 26.841090807077666  
2 bic 27.99278733132127  
2 iterations 89  
2 converged true  
2     1
2     2
2     3
3 coef 1, 1, 1, 1, 0, 0, 0  
3 ar_params [[-1.4296101261525473, 2.5315319963982015, 1.541536836147999], [0.5068978405697062, 0.34804164987971653, 0.27906793587515316], [-1.0150487527027767, -0.2032855566913086, 0.07866915491037613]]  
3 ma_params [[1.684265978492897, -1.0116180666097978, -5.533178263753073], [-1.0550984768730498, 1.5756063090213763, 4.70570346190122], [1.660449272138234, 0.6884049529205533, -0.26326075799465776]]  
3 exogenous_params    
3 seasonal_ar_params [[0.3038135044562906, -0.055637121723792274, -0.45848481298992416], [0.8796218186498189, -0.5098716183542696, -0.3679846957572214], [0.7588190526613598, -0.49764695771025447, -0.23842915354370808]]  
3 seasonal_ma_params    
3 period 4  
3 lag 0  
3 sigma [[0.04925768206601586, -0.06743723547426139, -0.061586897494505584], [-0.06743723547426139, 0.22449141784354268, 0.28364011938502687], [-0.061586897494505584, 0.28364011938502687, 0.41035204036308964]]  
3 aic -3.544378720752083  
3 bic -2.567726687519719  
3 iterations 100  
3 converged false  
3     1
3     2
3     3
VARMAX Example 3 Output Table (Columns 5-7)
id predict_expenditure predict_income predict_investment
1      
1      
1      
1      
1      
1      
1      
1      
1      
1      
1      
1      
1      
1 2142.78715878754 3092.86303423376 3673.84547642858
1 4144.01202399602 7019.73780801767 2413.26665396173
1 6182.11119125155 5848.79519783584 -1227.61804348869
2      
2      
2      
2      
2      
2      
2      
2      
2      
2      
2      
2      
2      
2 1879.13079317076 2309.21928969857 667.801515797637
2 2029.37000308685 2277.98815737177 568.158627956374
2 1590.12072329947 2093.70018052511 491.215852756901
3      
3      
3      
3      
3      
3      
3      
3      
3      
3      
3      
3      
3      
3 2255.14441988896 2673.97520019463 845.302048427789
3 2310.40934463343 2679.05646283002 888.074446679834
3 2333.56533607469 2727.31044779104 820.4016838113
series id = 3 does not converge. Convergence could possibly be improved by adding either more orders or more models.