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Fill in the table by preparing forecasts based on a five-year moving average, a three-year moving average, and exponential smoothing (w = 0.9 and w = 0.3). (Note: The exponential smoothing forecasts may be begun by assuming Yt + 1 = Yt.) Year 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Actual Demand 1,400 1,390 1,425 1,430 1,480 1,500 1,490 1,525 1,530 1,580 * Moving Average (5-year) (3-year) Exponential Smoothing (W = 0.9) (W = 0.3)

Fill in the table by preparing forecasts based on a five-year moving average, a three-year moving average, and exponential smoothing (w = 0.9 and w = 0.3). (Note: The exponential smoothing forecasts may be begun by assuming Yt + 1 = Yt.) Year 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Actual Demand 1,400 1,390 1,425 1,430 1,480 1,500 1,490 1,525 1,530 1,580 * Moving Average (5-year) (3-year) Exponential Smoothing (W = 0.9) (W = 0.3)

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Fill in the table by preparing forecasts based on a five-year moving average, a three-year moving average, and exponential smoothing (w = 0.9 and w = 0.3). (Note: The exponential smoothing forecasts may be begun by assuming Ŷt + 1 = Yt.) Year 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Actual Demand 1,400 1,390 1,425 1,430 1,480 1,500 1,490 1,525 1,530 1,580 * Moving Average (5-year) (3-year) Exponential Smoothing (W = 0.3) (W = 0.9)
Transcribed Image Text:Fill in the table by preparing forecasts based on a five-year moving average, a three-year moving average, and exponential smoothing (w = 0.9 and w = 0.3). (Note: The exponential smoothing forecasts may be begun by assuming Ŷt + 1 = Yt.) Year 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Actual Demand 1,400 1,390 1,425 1,430 1,480 1,500 1,490 1,525 1,530 1,580 * Moving Average (5-year) (3-year) Exponential Smoothing (W = 0.3) (W = 0.9)
Year (5-year) 2005 5,625 2006 2,025 2007 3,600 2,025 5,625 2008 2009 RMSE Square Error Moving Average (3-year) 3,025 400 1,225 625 4,225 O Exponential smoothing (w = 0.3) Exponential smoothing (w = 0.9) Exponential Smoothing (W = 0.9) (W = 0.3) 625 4,489 64 1,369 1,156 3,721 64 2,304 7,056 Based on the RMSE criterion, which of the forecasting methods is the most accurate? O Five-year moving average O Three-year moving average 2,601
Transcribed Image Text:Year (5-year) 2005 5,625 2006 2,025 2007 3,600 2,025 5,625 2008 2009 RMSE Square Error Moving Average (3-year) 3,025 400 1,225 625 4,225 O Exponential smoothing (w = 0.3) Exponential smoothing (w = 0.9) Exponential Smoothing (W = 0.9) (W = 0.3) 625 4,489 64 1,369 1,156 3,721 64 2,304 7,056 Based on the RMSE criterion, which of the forecasting methods is the most accurate? O Five-year moving average O Three-year moving average 2,601
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