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A B с 1 Trend and Seasonal Effects 3 Step 1. Complete tables to right 4 and below filling in yellow cells 5 with appropriate formulas. 123456789022 α = 0.3 Level 8 = 0.2 Trend Y = 0.5 Season 11 E F H M N P R W Actual Sales (Y) Season Year Average 1 Year 1 1 2 3 4 2 2 3 3 4 4 Average of Season Initial Values when M 4 (Quarterly): S₁ Actual 13 Period (Y) Base Value (L) Trend Season Squared Orange cells are the initial values that must also be computed. Y₁ average(Y S₂ = average(Y ■L₁ = Y₁/S₁ S3 = Y₁ average(YYYY Y4 S₁₂ = average (YYYY) (T) (S) Forecast Error Y. Error 14 1 500 15 2 560 Use formula for seasonal value: S = (Ys/Ls) + (1-7) S5-4 16 690 17 4 900 18 5 524 19 6 589 20 7 707 21 8 930 22 9 600 23 10 630 24 11 707 25 12 1020 26 13 613 27 14 641 The irena and seasonal forecasting model is an extension of the Trend Adjusted Exponential Smoothing model. In addition to a trend, the model also adds a smoothed adjustment for seasonality. This template is a quarterly model, where the number of seasons is set to 4. There are three smoothing constants associated with this model. Alpha is the smoothing constant for the basic level, delta smoothes the trend, and gamma smoothes the seasonal index. Again, the weighting or smoothing factors, alpha, delta and gamma can never exceed 1 and higher values put more weight on more icant time periode. La (Y/SM) + (1-α) (L+ T₁₁) TB (LL)+(1-B) T-1 S₁y (YL)+(1-y) St-M Ft+k = (Lt +K*T₁)* St-M+k Note 1: Y is actual demand, not "year". Note 2: k is # of periods in the past (typically = 1) 28 15 738 29 16 1079 30 17 31 MSE 32 33 Step 2. After calculating with the given alpha, beta and gamma, find the minimum 34 MSE by optimizing alpha, beta, and gamma using Excel's Solver tool. Submit your 35 work with only the resulting MINIMUM MSE solution.

A B с 1 Trend and Seasonal Effects 3 Step 1. Complete tables to right 4 and below filling in yellow cells 5 with appropriate formulas. 123456789022 α = 0.3 Level 8 = 0.2 Trend Y = 0.5 Season 11 E F H M N P R W Actual Sales (Y) Season Year Average 1 Year 1 1 2 3 4 2 2 3 3 4 4 Average of Season Initial Values when M 4 (Quarterly): S₁ Actual 13 Period (Y) Base Value (L) Trend Season Squared Orange cells are the initial values that must also be computed. Y₁ average(Y S₂ = average(Y ■L₁ = Y₁/S₁ S3 = Y₁ average(YYYY Y4 S₁₂ = average (YYYY) (T) (S) Forecast Error Y. Error 14 1 500 15 2 560 Use formula for seasonal value: S = (Ys/Ls) + (1-7) S5-4 16 690 17 4 900 18 5 524 19 6 589 20 7 707 21 8 930 22 9 600 23 10 630 24 11 707 25 12 1020 26 13 613 27 14 641 The irena and seasonal forecasting model is an extension of the Trend Adjusted Exponential Smoothing model. In addition to a trend, the model also adds a smoothed adjustment for seasonality. This template is a quarterly model, where the number of seasons is set to 4. There are three smoothing constants associated with this model. Alpha is the smoothing constant for the basic level, delta smoothes the trend, and gamma smoothes the seasonal index. Again, the weighting or smoothing factors, alpha, delta and gamma can never exceed 1 and higher values put more weight on more icant time periode. La (Y/SM) + (1-α) (L+ T₁₁) TB (LL)+(1-B) T-1 S₁y (YL)+(1-y) St-M Ft+k = (Lt +K*T₁)* St-M+k Note 1: Y is actual demand, not "year". Note 2: k is # of periods in the past (typically = 1) 28 15 738 29 16 1079 30 17 31 MSE 32 33 Step 2. After calculating with the given alpha, beta and gamma, find the minimum 34 MSE by optimizing alpha, beta, and gamma using Excel's Solver tool. Submit your 35 work with only the resulting MINIMUM MSE solution.

Advanced Engineering Mathematics
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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A B с 1 Trend and Seasonal Effects 3 Step 1. Complete tables to right 4 and below filling in yellow cells 5 with appropriate formulas. 123456789022 α = 0.3 Level 8 = 0.2 Trend Y = 0.5 Season 11 E F H M N P R W Actual Sales (Y) Season Year Average 1 Year 1 1 2 3 4 2 2 3 3 4 4 Average of Season Initial Values when M 4 (Quarterly): S₁ Actual 13 Period (Y) Base Value (L) Trend Season Squared Orange cells are the initial values that must also be computed. Y₁ average(Y S₂ = average(Y ■L₁ = Y₁/S₁ S3 = Y₁ average(YYYY Y4 S₁₂ = average (YYYY) (T) (S) Forecast Error Y. Error 14 1 500 15 2 560 Use formula for seasonal value: S = (Ys/Ls) + (1-7) S5-4 16 690 17 4 900 18 5 524 19 6 589 20 7 707 21 8 930 22 9 600 23 10 630 24 11 707 25 12 1020 26 13 613 27 14 641 The irena and seasonal forecasting model is an extension of the Trend Adjusted Exponential Smoothing model. In addition to a trend, the model also adds a smoothed adjustment for seasonality. This template is a quarterly model, where the number of seasons is set to 4. There are three smoothing constants associated with this model. Alpha is the smoothing constant for the basic level, delta smoothes the trend, and gamma smoothes the seasonal index. Again, the weighting or smoothing factors, alpha, delta and gamma can never exceed 1 and higher values put more weight on more icant time periode. La (Y/SM) + (1-α) (L+ T₁₁) TB (LL)+(1-B) T-1 S₁y (YL)+(1-y) St-M Ft+k = (Lt +K*T₁)* St-M+k Note 1: Y is actual demand, not "year". Note 2: k is # of periods in the past (typically = 1) 28 15 738 29 16 1079 30 17 31 MSE 32 33 Step 2. After calculating with the given alpha, beta and gamma, find the minimum 34 MSE by optimizing alpha, beta, and gamma using Excel's Solver tool. Submit your 35 work with only the resulting MINIMUM MSE solution.
Transcribed Image Text:A B с 1 Trend and Seasonal Effects 3 Step 1. Complete tables to right 4 and below filling in yellow cells 5 with appropriate formulas. 123456789022 α = 0.3 Level 8 = 0.2 Trend Y = 0.5 Season 11 E F H M N P R W Actual Sales (Y) Season Year Average 1 Year 1 1 2 3 4 2 2 3 3 4 4 Average of Season Initial Values when M 4 (Quarterly): S₁ Actual 13 Period (Y) Base Value (L) Trend Season Squared Orange cells are the initial values that must also be computed. Y₁ average(Y S₂ = average(Y ■L₁ = Y₁/S₁ S3 = Y₁ average(YYYY Y4 S₁₂ = average (YYYY) (T) (S) Forecast Error Y. Error 14 1 500 15 2 560 Use formula for seasonal value: S = (Ys/Ls) + (1-7) S5-4 16 690 17 4 900 18 5 524 19 6 589 20 7 707 21 8 930 22 9 600 23 10 630 24 11 707 25 12 1020 26 13 613 27 14 641 The irena and seasonal forecasting model is an extension of the Trend Adjusted Exponential Smoothing model. In addition to a trend, the model also adds a smoothed adjustment for seasonality. This template is a quarterly model, where the number of seasons is set to 4. There are three smoothing constants associated with this model. Alpha is the smoothing constant for the basic level, delta smoothes the trend, and gamma smoothes the seasonal index. Again, the weighting or smoothing factors, alpha, delta and gamma can never exceed 1 and higher values put more weight on more icant time periode. La (Y/SM) + (1-α) (L+ T₁₁) TB (LL)+(1-B) T-1 S₁y (YL)+(1-y) St-M Ft+k = (Lt +K*T₁)* St-M+k Note 1: Y is actual demand, not "year". Note 2: k is # of periods in the past (typically = 1) 28 15 738 29 16 1079 30 17 31 MSE 32 33 Step 2. After calculating with the given alpha, beta and gamma, find the minimum 34 MSE by optimizing alpha, beta, and gamma using Excel's Solver tool. Submit your 35 work with only the resulting MINIMUM MSE solution.
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