(c) Are the results the same if you apply MAE as the measure of accuracy? (Round your answers to two decimal places.) , and using a = 0.2 MAE is 3.05 X , so the results are not the same as applying MSE as our measure of Using a = 0.1 MAE is 3.02 accuracy. (d) What are the results if MAPE is used? (Round your answers to two decimal places.) X %, and using a = 0.2 MAPE is 15.33 X %, so we would prefer a smoothing constant of 0.1 v Using a = 0.1 MAPE Is 21.11
(c) Are the results the same if you apply MAE as the measure of accuracy? (Round your answers to two decimal places.) , and using a = 0.2 MAE is 3.05 X , so the results are not the same as applying MSE as our measure of Using a = 0.1 MAE is 3.02 accuracy. (d) What are the results if MAPE is used? (Round your answers to two decimal places.) X %, and using a = 0.2 MAPE is 15.33 X %, so we would prefer a smoothing constant of 0.1 v Using a = 0.1 MAPE Is 21.11
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Please correct my answers for c and d
Transcribed Image Text:(b) Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of a = 0.1 or a = 0.2 for the gasoline sales time serles? (Round your answers
to two decimal places.)
Using a - 0.1 MSE is 12.16
, and using a = 0.2 MSE is 11.66
, so we would prefer a smnoothing constant of 0.2 v
(c) Are the results the same if you apply MAE as the measure of accuracy? (Round your answers to two decimal places.)
and using a = 0.2 MAE is 3.05
so the results are not
the same as applying MSE as our measure of
Using a - 0.1 MAE is 3.02
accuracy.
(d) What are the results if MAPE is used? (Round your answers to two decimal places.)
X %, and using a = 0.2 MAPE is 15.33
X %, so we would prefer a smoothing constant of 0.1
Using a - 0.1 MAPE is 21.11
Transcribed Image Text:(a) Show the exponential smoothing forecasts using a - 0.1. (Round your answers to three decimal places.)
Time Series
Value
Week
Forecast
1.
17
2
21
17
20
17.4
4
24
17.66
5
18
18.294
6
17
18.2646
20
18.13814
17
18.324
9
23
18.191
10
21
18.672
11
15
18.905
12
23
18.514
3.
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