please solve the provided question with reaponse variable as y and predictor variables as x1 and x2 and a total of 30 observations collected in data set. holdout method with linear model with exponential model a-1. Use the training set to estimate Models 1 and 2. Note: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places. Predictor Variable Model 1 (Linear) Constant -146.71 -18.11 26.93 X1 X2 RMSE a-2. Calculate the RMSE of the two models in the validation set. Note: Do not round intermediate calculations and round final answers to 2 decimal places. x1 533.86 20 3 104.84 15 4 64.89 20 5 159.61 16 6 43.06 13 7 4.27 13 8 736.56 15 9 64.89 20 1y 10 10.64 11 76.90 12 4.89 13 80.90 14 224.17 15 45.75 16 8.13 17 319.97 18 48.61 19 564.67 20 63.00 21 152.39 22 13.34 11 13 18 15 13 17 18 27 451.65 17 28 10.34 18 29 32.70 12 23 28.80 24 37.56 25 105.62 26 44.05 20 18 11 11 12 16 17 13 19 12 30 19.21 31 63.00 32 2.45 33 2.48 34 50.34 35 29.31 36 33.75 37 196.28 38 943.12 39 7.25 40 89.73 41 32.91 42 43 14 15 16 20 17 17 16 17 13 10 15 12 Model 1 (Linear) x2 30 20 23 21 16 13 30 23 22 20 13 16 19 25 17 30 25 27 25 24 14 22 15 26 21 28 21 13 12 16 12 15 21 20 12 29 30 12 25 18 Model 2 (Exponential) 193.11 -2.71 X -0.15 x 0.22 Model 2 (Exponential) 0.83
please solve the provided question with reaponse variable as y and predictor variables as x1 and x2 and a total of 30 observations collected in data set. holdout method with linear model with exponential model a-1. Use the training set to estimate Models 1 and 2. Note: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places. Predictor Variable Model 1 (Linear) Constant -146.71 -18.11 26.93 X1 X2 RMSE a-2. Calculate the RMSE of the two models in the validation set. Note: Do not round intermediate calculations and round final answers to 2 decimal places. x1 533.86 20 3 104.84 15 4 64.89 20 5 159.61 16 6 43.06 13 7 4.27 13 8 736.56 15 9 64.89 20 1y 10 10.64 11 76.90 12 4.89 13 80.90 14 224.17 15 45.75 16 8.13 17 319.97 18 48.61 19 564.67 20 63.00 21 152.39 22 13.34 11 13 18 15 13 17 18 27 451.65 17 28 10.34 18 29 32.70 12 23 28.80 24 37.56 25 105.62 26 44.05 20 18 11 11 12 16 17 13 19 12 30 19.21 31 63.00 32 2.45 33 2.48 34 50.34 35 29.31 36 33.75 37 196.28 38 943.12 39 7.25 40 89.73 41 32.91 42 43 14 15 16 20 17 17 16 17 13 10 15 12 Model 1 (Linear) x2 30 20 23 21 16 13 30 23 22 20 13 16 19 25 17 30 25 27 25 24 14 22 15 26 21 28 21 13 12 16 12 15 21 20 12 29 30 12 25 18 Model 2 (Exponential) 193.11 -2.71 X -0.15 x 0.22 Model 2 (Exponential) 0.83
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
Transcribed Image Text:please solve the provided question with reaponse variable as y and predictor
variables as x1 and x2 and a total of 30 observations collected in data set.
holdout method with linear model with exponential model
a-1. Use the training set to estimate Models 1 and 2.
Note: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.
Predictor Variable Model 1 (Linear) Model 2 (Exponential)
Constant
-146.71 X
-18.11
26.93
X1
X2
a-2. Calculate the RMSE of the two models in the validation set.
Note: Do not round intermediate calculations and round final answers to 2 decimal places.
RMSE
1 y
x1
2 533.86 20
3 104.84 15
4 64.89
20
5 159.61 16
6 43.06
7 4.27
8 736.56 15
9 64.89
20
10 10.64
11 76.90
12 4.89
13 80.90
14 224.17 12
15 45.75
16
17
16 8.13
17 319.97
13
13
20
18
22 13.34
23 28.80
24 37.56
11
11
13
19
12
18 48.61
19 564.67
20 63.00
11
21 152.39 13
18
15
13
25 105.62 17
26 44.05
18
27 451.65 17
28 10.34
18
29 32.70
12
30 19.21
14
31 63.00
15
32 2.45
16
33 2.48
20
34 50.34
17
35 29.31
17
36 33.75
16
37 196.28 17
38 943.12 13
39 7.25
10
40 89.73
15
41 32.91
12
42
43
44
45
Model 1 (Linear)
x2
30
20
23
21
16
13
30
23
22
20
13
16
19
25
17
30
25
27
25
24
14
22
15
26
21
28
21
13
12
16
12
15
21
20
12
29
30
12
25
18
-2.71 X
-0.15 x
0.22
193.11
Model 2 (Exponential)
0.83 x
Transcribed Image Text:1
2 533.86
y
B 104.84
159.61
1 05 0 16
x1
26 44.05
27 451.65
28 10.34
20
4 64.89
5
6 43.06
7 4.27
8 736.56
9
64.89
10 10.64
11 76.90
18
12 4.89
11
13 80.90
11
14 224.17
12
15 45.75
16
16 8.13
17
17 319.97 13
18 48.61
19
19 564.67
20 63.00
21 152.39
22 13.34
23 28.80
24 37.56
25 105.62
15
20
16
13
315
13
15
20
20
00
12
11
13
18
15
13
17
18
17
18
29 32.70
12
30 19.21
14
31 63.00
15
32 2.45
16
33 2.48
20
34 50.34
17
35 29.31
17
36 33.75
16
37 196.28
17
38 943.12 13
39 7.25
10
40 89.73
15
41 32.91
12
42
43
44
45
x2
30
20
23
21
16
13
30
23
22
20
13
16
19
25
17
30
25
27
25
24
14
22
15
26
21
28
21
13
12
16
12
15
21
20
12
29
30
12
25
18
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