Metode ARIMA Box-Jenkins - · PDF fileMetode ARIMA Box-Jenkins Model ARIMA Box-Jenkins...
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Metode ARIMA Box-Jenkins
Model ARIMA Box-Jenkins Model ARIMA Box-Jenkins Identification of STATIONER TIME SERIES Estimation of ARIMA model Diagnostic Check of ARIMA model Forecasting
Estimation and Testing parameter ARIMA model
t-values and prob-values for testing parameter model ARIMA
Parameters ARIMA
model estimates
Diagnostic Checking of ARIMA model … [white noise residual]
Ljung-Box statistic for testing white noise residual
ACF of residual
Forecasting of ARIMA(p,d,q) model
Forecasting of AR(1) model
or
Forecasting of MA(1) model Forecasting of MA(1) model
Example: Daily readings of viscosity of Chemical Product XB-77-5 [Bowerman and O’Connell, pg. 471]
Example: IDENTIFICATION step [stationary, ACF and PACF]
ACF PACF
Stationer time series
Dies down [sinusoidal] Cuts off after lag 2
Example: ESTIMATION and DIAGNOSTIC CHECK step
Estimationand Testingparameter
Diagnostic Check (white
noise residual)
Example: DIAGNOSTIC CHECK step … [Normality test of residuals]
Example: FORECASTING step [MINITAB output]
Calculation: FORECASTING (FITS and FORECAST) [continued]
MINITAB command: IDENTIFICATION Step
Plot DataPlot Data stationarity data
ACF & PACF data to find tentative
ARIMA model
IDENTIFICATION Step: Time Series Plot …
IDENTIFICATION Step: ACF data …
IDENTIFICATION Step: PACF data …
MINITAB command: ESTIMATION, DIAGNOSTIC CHECK & FORECASTING Step
Estimation, Diagnostic Check and Forecasting
MINITAB command: Normality test for residual