Fill the table by calculating the root mean square error (RMSE) for each of the methods.Square ErrorMoving AverageExponential Smoothing(W = 0.9)Year(5-year)(3-year)(W = 0.3)2005252525200610016910036200762552925636120081,6003,0254841,0892,3041,08920091,849729RMSE

The following table for square error is given. Square Error…

Fill the table by calculating the root mean square error (RMSE) for each of the methods. Square Error Moving Average (5-year) Exponential Smoothing Year |(3-year) (W = 0.9) (W = 0.3) 2005 25 9 25 25 2006 100 169 100 36 2007 625 529 256 361 2008 1,600 3,025 1,089 484 1,089 2009 1,849 729 2,304 RMSE

Fill the table by calculating the root mean square error (RMSE) for each of the methods. Square Error Moving Average (5-year) Exponential Smoothing Year |(3-year) (W = 0.9) (W = 0.3) 2005 25 9 25 25 2006 100 169 100 36 2007 625 529 256 361 2008 1,600 3,025 1,089 484 1,089 2009 1,849 729 2,304 RMSE

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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Concept explainers

Estimation

A new framework of data analysis where the new statistical methods are used for interpreting the results and analyzing the data is known as estimation in statistics.

Question

100%

Fill the table by calculating the root mean square error (RMSE) for each of the methods.
Square Error
Moving Average
Exponential Smoothing
(W = 0.9)
Year
(5-year)
(3-year)
(W = 0.3)
2005
25
25
25
2006
100
169
100
36
2007
625
529
256
361
2008
1,600
3,025
484
1,089
2,304
1,089
2009
1,849
729
RMSE

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