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262 CAPITOLO 4. ANALISI E PREVISIONE DI SERIE STORICHE res
4.6. ESERCIZI SULLE SERIE STORICHE 263 da cui abbandoniamo Weibull. Questi calcoli permettono ad esempio di calcolare il valore minimo delle esportazioni al 90%, per i mesi successivi ai dati noti: qnorm(0.1,m.g,s.g)+min(res)-10 [1] -7115085 che va aggiunto alla predizione pred.12 gen06 feb06 mar06 36833568 42080786 48266104 (ecc:) per cui il valore minimo delle esportazioni al 90% è gen06 feb06 mar06 29.718.483 34.965.701 41.151.019 (ecc:) E’molto più realistico. In verità andrebbe peggiorato un po’per la seguente ragione: abbiamo usato tutti i residui per la stima della gaussiana ma gli ultimi sono maggiori dei primi: par(mfrow=c(1,1)) ts.plot(res) per cui sarebbe più onesto usare solo i residui diciamoo dal 2000 in poi. Lasciamo il calcolo per esercizio. Consideriamo ora la serie Mot. Esercizio: Ripetere tutti i ragionamenti precedenti per la serie Mot, usando HW come modello. Nota: al posto del comando res
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Elementi di Probabilità, Statistic
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iv INDICE 1.2.16 Disuguaglianza di
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vi INDICE 4.2.11 Densità spettrale
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viii INDICE 6.3.7 Loadings, rotazio
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x PREFAZIONE
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2 CAPITOLO 1. ELEMENTI DI CALCOLO D
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10 CAPITOLO 1. ELEMENTI DI CALCOLO
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114 CAPITOLO 2. ELEMENTI DI STATIST
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146 CAPITOLO 3. PROCESSI STOCASTICI
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190 CAPITOLO 4. ANALISI E PREVISION
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Page 276 and 277: 266 CAPITOLO 5. SISTEMI MARKOVIANI
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312 CAPITOLO 5. SISTEMI MARKOVIANI
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320 CAPITOLO 6. STATISTICA MULTIVAR
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