College Algebra (MindTap Course List)
College Algebra (MindTap Course List)
12th Edition
ISBN: 9781305652231
Author: R. David Gustafson, Jeff Hughes
Publisher: Cengage Learning
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Transcribed Image Text:e. Use an ARIMA model to forecast CPI, then use these to forecast the (non-adjusted) takings for Victoria until the end of 2017. Hint: You will have to use the new_data argument to forecast(). f. What sources of uncertainty have not been taken into account in the prediction intervals?
[画像:4. Dynamic regression (adapted from Q10.4 in Hyndman & Athanasopoulos) This exercise concerns aus_accommodation: the total quarterly takings from accommodation and the room occupancy level for hotels, motels, and guest houses in Australia, between January 1998 and June 2016. Total quarterly takings are in millions of Australian dollars. a. Perform inflation adjustment for Takings (using the CPI column), creating a new column in the tsibble called Adj Takings. b. For each state, fit a dynamic regression model of Adj Takings with seasonal dummy variables, a piecewise linear time trend with one knot at 2008 Q1, and ARIMA errors. c. What model was fitted for the state of Victoria? Does the time series exhibit constant seasonality? d. Check that the residuals of the model in c) look like white noise.]
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Transcribed Image Text:4. Dynamic regression (adapted from Q10.4 in Hyndman & Athanasopoulos) This exercise concerns aus_accommodation: the total quarterly takings from accommodation and the room occupancy level for hotels, motels, and guest houses in Australia, between January 1998 and June 2016. Total quarterly takings are in millions of Australian dollars. a. Perform inflation adjustment for Takings (using the CPI column), creating a new column in the tsibble called Adj Takings. b. For each state, fit a dynamic regression model of Adj Takings with seasonal dummy variables, a piecewise linear time trend with one knot at 2008 Q1, and ARIMA errors. c. What model was fitted for the state of Victoria? Does the time series exhibit constant seasonality? d. Check that the residuals of the model in c) look like white noise.
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