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Time Series Analysis - Worked Example - Part B

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Time Series Analysis - Worked Example - Part B
This exercise delves into time series analysis by fitting different models, such as AR(1), AR(3), and ARMA(1,1), to the provided data. It involves determining the best fit model and using it to predict future values. Additionally, it requires constructing and analyzing the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) for the residuals of the selected model. The Ljung-Box Portmanteau test is then performed to assess the model’s appropriateness. Overall, this exercise offers a comprehensive approach to understanding and applying time series models to real-world data.
This exercise delves into time series analysis by fitting different models, such as AR(1), AR(3), and ARMA(1,1), to the provided data. It involves determining the best fit model and using it to predict future values. Additionally, it requires constructing and analyzing the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) for the residuals of the selected model. The Ljung-Box Portmanteau test is then performed to assess the model’s appropriateness. Overall, this exercise offers a comprehensive approach to understanding and applying time series models to real-world data.