choices: a. true b. false c. others (specify) 1. Holt’s linear method is very applicable for longer forecast. 2. The best smoothing parameters, α and β^*, for Holt's linear model is the values from -1 and 1 that can minimize SSE. 3. In the PACF, there are three spikes decreasing with the lag, and then no significant spikes thereafter. This suggests a possible AR(3) model.

choices: a. true b. false c. others (specify) 1. Holt’s linear method is very applicable for longer forecast. 2. The best smoothing parameters, α and β^*, for Holt's linear model is the values from -1 and 1 that can minimize SSE. 3. In the PACF, there are three spikes decreasing with the lag, and then no significant spikes thereafter. This suggests a possible AR(3) model.

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section: Chapter Questions

Problem 42P: The file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars)...

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Similar questions

Under what conditions might a firm use multiple forecasting methods?
The file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars) through credit unions. a. Use these data to forecast consumer revolving credit through credit unions for the next 12 months. Do it in two ways. First, fit an exponential trend to the series. Second, use Holts method with optimized smoothing constants. b. Which of these two methods appears to provide the best forecasts? Answer by comparing their MAPE values.
The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your model. What makes this time series more challenging to forecast?
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