Reference no: EM133694189
Data-driven Decision Making and Forecasting
Assessment - Fitting and evaluating ARIMA and VAR time series models
Your Tasks
In Class: Compare fitting a SARIMA model to fitting an ARMA model to residuals from a Prophet model, for two time series. Discuss the advantages and disadvantages of the two approaches.
Assessment Description
In class: Two time series will be given to you at the start of your usual 3-hour class in Week 9, together with specific questions to answer. You will be expected to use Exploratory and Excel
In class:
At the beginning of the class, your lecturer will provide you with a dataset and a series of questions to answer. You will create a Word document with the answers to questions. At the end of class, submit your Word file via MyKBS.
Part A: Fit SARIMA models to the two time series and provide plots of the time series and predictions. Provide the acfs of the residuals.
Part B: Obtain residuals from Prophet models and fit ARMA models to these residuals.
Part C: Discuss the advantages and disadvantages of the two approaches.
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Fitted sarima models to the two time series
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Obtained residuals from prophet models
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Plot of the time series and predictions
: Provide the acfs of the residuals, Plot of the time series and predictions and Obtain residuals from Prophet models and fit ARMA models to these residuals
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Advantages and disadvantages of arma and sarima model
: Discuss the advantages and disadvantages of the ARMA model and SARIMA model, Obtain residuals from Prophet models and fit ARMA models to these residuals
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Advantages and disadvantages of sarima model
: Discuss the advantages and disadvantages of SARIMA model to fitting an ARMA model, Data-driven Decision Making and Forecasting
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Arma model to residuals from a prophet model
: ARMA model to residuals from a Prophet model, Fitting and evaluating ARIMA and VAR time series models Assessment - Data-driven Decision Making and Forecasting
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