Tham khảo tài liệu 'process or product monitoring and control_9', kỹ thuật - công nghệ, điện - điện tử phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | . Model Identification for Southern Oscillations Data hW ENGINEERING STATISTICS HANDBOOK TOOLS raids ISEAtCH back NEKT 6. Process or Product Monitoring and Control . Introduction to Time Series Analysis . Univariate Time Series Models . Box-Jenkins Model Identification . Model Identification for Southern Oscillations Data Example for Southern Oscillations We show typical series of plots for the initial model identification stages of Box-Jenkins modeling for two different examples. The first example is for the southern oscillations data set. We start with the run sequence plot and seasonal subseries plot to determine if we need to address stationarity and seasonality. Run Sequence Plot The run sequence plot indicates stationarity. http div898 handbook pmc section4 1 of 3 5 1 2006 10 35 28 AM . Model Identification for Southern Oscillations Data Seasonal Subseries Plot The seasonal subseries plot indicates that there is no significant seasonality. Since the above plots show that this series does not exhibit any significant non-stationarity or seasonality we generate the autocorrelation and partial autocorrelation plots of the raw data. Autocorrelation Plot Southern Oscillations The autocorrelation plot shows a mixture of exponentially decaying http div898 handbook pmc section4 2 of 3 5 1 2006 10 35 28 AM . Model Identification for Southern Oscillations Data and damped sinusoidal components. This indicates that an autoregressive model with order greater than one may be appropriate for these data. The partial autocorrelation plot should be examined to determine the order. Partial Autocorrelation Plot B Lag The partial autocorrelation plot suggests that an AR 2 model might be appropriate. In summary our intial attempt would be to fit an AR 2 model with no seasonal terms and no differencing or trend removal. Model validation should be performed before accepting .
