Georgia Institute Of Technology - ISYE 6501hw4 ( ALL SOLUTIONS ARE 100% CORRECT )

Document Content and Description Below

ISYE 6501 19SP1 HW 4 solution Question 7.1 Describe a situation or problem from your job, everyday life, current events, etc., for which exponential smoothing would be appropriate. What data would ... you need? Would you expect the value of  (the first smoothing parameter) to be closer to 0 or 1, and why? Solution 7.1 Exponential smoothing would be appropriate to be used in forecasting USA Gross domestic product (GDP). The Gross domestic Product (GDP) is the market value of all final goods and services produced within a country in a given period of time. For USA quarterly GDP data, we can download the Federal Reserve website (​https://fred.stlouisfed.org/series/GDP​). I expect the smoothing parameter, alpha, is closer 1 in USA GDP forecasting as the economy of USA. It means that more weight is given to the actual data. As US economy is huge and has many types goods and service produces, the randomness of overall US economy should be less. Question 7.2 Using the 20 years of daily high temperature data for Atlanta (July through October) from Question 6.2 (file temps.txt), build and use an exponential smoothing model to help make a judgment of whether the unofficial end of summer has gotten later over the 20 years. (Part of the point of this assignment is for you to think about how you might use exponential smoothing to answer this question. Feel free to combine it with other models if you’d like to. There’s certainly more than one reasonable approach.) Note: in R, you can use either HoltWinters (simpler to use) or the smooth package’s es function (harder to use, but more general). If you use es, the Holt-Winters model uses model=”AAM” in the function call (the first and second constants are used “A”dditively, and the third (seasonality) is used “M”ultiplicatively; the documentation doesn’t make that clear).Solution 7.2 HoltWinters function is used to generate 4 exponential smoothing models: single, double, triple with additive seasonality and triple with multiplicative seasonality. The results from exponential smoothing models do not support the unofficial end of summer has gotten later over the 20 years. Sample result & chart from Triple exponential smoothing model with multiplicative seasonality. It is observed that there is not trend variation in the temperature data set. [Show More]

Last updated: 1 year ago

Preview 1 out of 48 pages