Problem 2: Curve Fitting: The data points (xi, Yi) were observed (-3,3), (-1, –1), (1,3) and (3, 15). -3 Thus, the x-values and y-values are: = 1 and ỹ = 1 The plot shows these data points and both the best-fit line 3 15. 16 and the best-fit parabola. 14 a. Record the design matrix D you would use to find the best-fit line. 12 10 y = Bo + B1 x D = 4 Given for free: The product D™D is DTD = -2 -3 -2 -1 1 2 3 X-axis b. Find the inverse of the product D" D -唱9 (D"D)-1 and record it in the box. c. Solve the normal equation ( D"D)B = D"ỷ to find the vector B = with the best-fit parameters for the line. Hint: D"ÿ = Parameter vector ß. d. It can be shown that the best-fit line gives the estimates Ўest Find the error vector: y- ỹest · Then give the root mean square error. RMSE = Error vector = Parabolic design matrix D: e. Let's start over and try a parabolic fit. Record the design matrix D you would use to find the best-fit parabola y = Bo + B1 x + B2 x2 D f. Nice! The parabola fits perfectly, and you would find B = 2 Using this parabola, estimate y(2) = DDDD N O O DODD DDDD DDDD DDDD

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ISBN:9780470458365
Author:Erwin Kreyszig
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Chapter2: Second-order Linear Odes
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Problem 2: Curve Fitting: The data points (xi, y;) were observed (-3,3), (-1,–1), (1,3) and (3, 15).
-3"
31
Thus, the x-values and y-values are: X =
and ý =
The plot shows these data points and both the best-fit line
3.
15
16
and the best-fit parabola.
14
a. Record the design matrix D you would use to find the best-fit line.
12
****
10
8
y = Bo + B1 x
D =
4
2
[4
Given for free: The product D"D is D"D =
-2
-3
-2
-1
1
3
х-ахis
b. Find the inverse of the product DT D
(D"D)-1 :
-E到
and record it in the box.
c. Solve the normal equation ( D"D)B = D"ỷ to find the vector B =
with the best-fit parameters for the line.
Hint: D'ÿ = 40l
Parameter vector B.
d. It can be shown that the best-fit line gives the estimates
ỹest =
Find the error vector: ý - ỹest ·
7
Then give the root mean square error.
RMSE =
Error vector =
Parabolic design matrix D:
e. Let's start over and try a parabolic fit. Record the design matrix D
you would use to find the best-fit parabola y = Bo + B1 x + B2 x2
D =
f. Nice! The parabola fits perfectly, and you would find B
= 2. Using this parabola, estimate y(2) =
DDDD
ODDO
DD DD
DDDD
DDDI
Transcribed Image Text:Problem 2: Curve Fitting: The data points (xi, y;) were observed (-3,3), (-1,–1), (1,3) and (3, 15). -3" 31 Thus, the x-values and y-values are: X = and ý = The plot shows these data points and both the best-fit line 3. 15 16 and the best-fit parabola. 14 a. Record the design matrix D you would use to find the best-fit line. 12 **** 10 8 y = Bo + B1 x D = 4 2 [4 Given for free: The product D"D is D"D = -2 -3 -2 -1 1 3 х-ахis b. Find the inverse of the product DT D (D"D)-1 : -E到 and record it in the box. c. Solve the normal equation ( D"D)B = D"ỷ to find the vector B = with the best-fit parameters for the line. Hint: D'ÿ = 40l Parameter vector B. d. It can be shown that the best-fit line gives the estimates ỹest = Find the error vector: ý - ỹest · 7 Then give the root mean square error. RMSE = Error vector = Parabolic design matrix D: e. Let's start over and try a parabolic fit. Record the design matrix D you would use to find the best-fit parabola y = Bo + B1 x + B2 x2 D = f. Nice! The parabola fits perfectly, and you would find B = 2. Using this parabola, estimate y(2) = DDDD ODDO DD DD DDDD DDDI
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