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ARIMA(0,1,1) modeli – IMA(1,1)( 1 B ) Y (1 B)t 1t111Y tY t1 t 1 t1 Integrirani model pomičnih prosjeka Y t ~ IMA(1,1) → Y t =(1-B)Y t je stacionaranMA(1)• ACF Y t opadaju veoma sporo (nestacionarnost)• ACF Y t (stacionaran) ima karakteristike MA(1)procesa, tj. iščezava nakon pomaka k=1
Proces Y t =Y t-1 + t -0,75 t-1Autocorrelation FunctionY(Standard errors are white-noise estimates)Lag Corr. S.E.Q p1 +,652 ,070286,23 0,0002 +,586 ,0700156,2 0,0003 +,560 ,0698220,6 0,0004 +,571 ,0697287,9 0,000Partial Autocorrelation Function(Standard errors assume AR order of k-1)Lag Corr. S.E.1 +,652 ,07072 +,280 ,07073 +,194 ,07074 +,200 ,0707Y5 +,535 ,0695347,1 0,0005 +,082 ,07076 +,541 ,0693408,2 0,0006 +,124 ,07077 +,481 ,0691456,5 0,0007 -,021 ,07078 +,504 ,0689510,1 0,0008 +,100 ,07079 +,507 ,0688564,4 0,0009 +,082 ,070710 +,450 ,0686607,4 0,00010 -,054 ,070711 +,467 ,0684654,1 0,00012 +,416 ,0682691,3 0,00000-1,0 -0,5 0,0 0,5 1,0Conf. Limit11 +,082 ,070712 -,070 ,07070-1,0 -0,5 0,0 0,5 1,0Conf. Limit
Page 1 and 2: Mješoviti ARIMA modelPredavanje 5
Page 4 and 5: Modeli stacionarnih vremenskih nizo
Page 6 and 7: tptptttZZZZ ...22116tptptttZZZZ ...
Page 8 and 9: ARMA(p,q)( B ) Z ( B)tt(B)=1- - ppj
Page 10 and 11: Nestacionaran ARMA proces polinom (
Page 12 and 13: Integrirani mješoviti ARMA modeld(
Page 14 and 15: ARIMA proces ARIMA(0,1,0)1 B Z t t1
Page 16 and 17: ARIMA proces Prikladan za opisivanj
Page 18 and 19: Proces slučajnog pomakaYt Y t(1 B)
Page 22 and 23: Diferencirani proces (1-B)Y t = t -
Page 24 and 25: Nestacionarnost u varijanci iautoko
Page 26 and 27: Transformacije stabilizacije varija
Page 34 and 35: Box-Jenkinsov pristup odabiramodela
Page 36 and 37: Box-Jenkinsov pristupEmpirijske ana
Page 38 and 39: Box-Jenkinsov pristup najčešće k
Page 40 and 41: Box-Jenkinsov pristupProvodi se u k
Page 42 and 43: Faza identifikacije Odabir “poče
Page 44 and 45: Osnovni oblici teorijskih funkcija
Page 46 and 47: Faza procjenjivanja Procjene parama
Page 48 and 49: Faza procjenjivanjaKriteriji uspore
Page 50 and 51: Faza procjenjivanjaStacionarnost i
Page 52 and 53: Faza dijagnostičkog provjeravanja
Page 58 and 59: Odabir najboljeg modela velik broj
Page 60 and 61: Odabir najboljeg modela Mjere......
Page 62 and 63: Odabir najboljeg modelaAIC2lnLMSBC2
Page 64 and 65: Prognostičke pogreške koje se naj
Page 66 and 67: Faza prognoziranja Glavna ''zadaća
Page 68 and 69: Faza prognoziranjaDva izvora pogre
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Faza prognoziranja Optimalne progno
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Ispis EViews:Dinamičke prognoze Mu
Page 74 and 75:
Ispis EViews:800700600500400Forecas
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Ispis EViews:76
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Ispis EViews: Proporcija pristranos
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Ispis EViews: Proporcija kovarijanc
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Primjer Box-Jenkins metodologije Re
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Procjena ARIMA(1,1,0) modela85
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Procjena ARIMA(2,1,1) modela87
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