Non-Seasonal box-Jenkins models
1 Non-Seasonal Box-Jenkins Models
Four-step iterative procedures 1)Model Identification Parameter estimation 234 Diagnostic Checking Forecasting
2 Four-step iterative procedures 1) Model Identification 2) Parameter Estimation 3) Diagnostic Checking 4) Forecasting
Step One: Model Identification
3 Step One: Model Identification
Model identification I. Stationarit I. Theoretical autocorrelation function (TAC II. Theoretical Partial autocorrelation Function(TPAc IV. Sample partial Autocorrelation Function (SPAC V. Sample autocorrelation Function (SAC
4 Model Identification I. Stationarity II. Theoretical Autocorrelation Function (TAC) III. Theoretical Partial Autocorrelation Function (TPAC) IV. Sample Partial Autocorrelation Function (SPAC) V. Sample Autocorrelation Function (SAC)
Stationarity (D A sequence of jointly dependent random variables -oo<t<o is called a time series
5 Stationarity (I) A sequence of jointly dependent random variables is called a time series {y : − t } t