Least squares method : approximation of a cubic polynomial

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Discussion Overview

The discussion revolves around the approximation of a cubic polynomial using the least squares method, specifically applied to a set of given points. Participants explore the derivation of the polynomial coefficients through different approaches, including direct calculation of partial derivatives and the use of normal equations.

Discussion Character

  • Technical explanation, Mathematical reasoning, Debate/contested

Main Points Raised

  • One participant outlines the process of finding a cubic polynomial that minimizes the sum of squared differences between the polynomial values and given data points.
  • Another participant confirms the solution obtained using the normal equation method and notes a discrepancy in the polynomial obtained from the derivative method.
  • Participants discuss the residuals calculated from both methods, indicating that one method yields a lower residual than the other, suggesting a potential calculation error.
  • One participant revises their polynomial after checking calculations and questions whether the results should be identical or approximately the same.
  • Another participant notes that the values of the polynomial at specific points, such as \(x=0\), do not match the given data, raising questions about the nature of polynomial approximation.
  • There is a discussion about the sensitivity of results to rounding errors and the expectation that a cubic polynomial can only perfectly fit four points out of five.

Areas of Agreement / Disagreement

Participants express uncertainty regarding the consistency of results from different methods and whether the approximations should yield identical polynomials. There is no consensus on the necessity of matching specific polynomial values at given points.

Contextual Notes

Participants highlight that the least squares method aims to minimize the overall error, which may lead to slight discrepancies in polynomial values at certain points when more data points than the polynomial degree are used.

mathmari
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Hey! :o

I want to determine an approximation of a cubic polynomial that has at the points $$x_0=-2, \ x_1=-1, \ x_2=0 , \ x_3=3, \ x_4=3.5$$ the values $$y_0=-33, \ y_1=-20, \ y_2=-20.1, \ y_3=-4.3 , \ y_4=32.5$$ using the least squares method.

So we are looking for a cubic polynomial $p(x)$ such that $$\sum_{i=0}^4\left (p(x_i)-y_i\right )^2$$ is minimal, right? (Wondering) Let $p(x)=a_3x^3+a_2x^2+a_1x+a_0$. Then we get the following sum:
\begin{align*}\sum_{i=0}^4\left (p(x_i)-y_i\right )^2=&\left (-8a_3+4a_2-2a_1+a_0+33\right )^2+\left (-a_3+a_2-a_1+a_0+20\right )^2+\left (a_0+20.1\right )^2 \\ & +\left (27a_3+9a_2+3a_1+a_0+4.3\right )^2 +\left (42.875a_3+12.25a_2+3.5a_1+a_0-32.5\right )^2\end{align*}

Now we calculate the partial derivatives in respect to each $a_i$ and then we set these equal to $0$. In that we get a system of equations.

Let this sum be $S$.

We get the following partial derivatives:

\begin{align*}\frac{\partial{S}}{\partial{a_0}}=&2\left (-8a_3+4a_2-2a_1+a_0+33\right )+2\left (-a_3+a_2-a_1+a_0+20\right )\\ & +2\left (a_0+20.1\right ) +2\left (27a_3+9a_2+3a_1+a_0+4.3\right ) +2\left (42.875a_3+12.25a_2+3.5a_1+a_0-32.5\right )\\ = &89.8 + 10 a_0 + 7 a_1+ 52.5 a_2 + 121.75 a_3\end{align*}

\begin{align*}\frac{\partial{S}}{\partial{a_1}}=&2\left (-8a_3+4a_2-2a_1+a_0+33\right )\cdot 2+2\left (-a_3+a_2-a_1+a_0+20\right )\cdot (-1) \\ & +2\left (27a_3+9a_2+3a_1+a_0+4.3\right )\cdot 3 +2\left (42.875a_3+12.25a_2+3.5a_1+a_0-32.5\right )\cdot 3.5 \\ = & -109.7 + 15 a_0 + 36.5 a_1 + 153.75 a_2 + 432.125 a_3\end{align*}

\begin{align*}\frac{\partial{S}}{\partial{a_2}}=&2\left (-8a_3+4a_2-2a_1+a_0+33\right )\cdot 4+2\left (-a_3+a_2-a_1+a_0+20\right ) \\ & +2\left (27a_3+9a_2+3a_1+a_0+4.3\right )\cdot 9 +2\left (42.875a_3+12.25a_2+3.5a_1+a_0-32.5\right )\cdot 12.25\\ = & -414.85 + 52.5 a_0 + 121.75 a_1 + 496.125 a_2 + 1470.44 a_3 \end{align*}

\begin{align*}\frac{\partial{S}}{\partial{a_3}}=&2\left (-8a_3+4a_2-2a_1+a_0+33\right )\cdot (-8)+2\left (-a_3+a_2-a_1+a_0+20\right )\cdot (-1) \\ & +2\left (27a_3+9a_2+3a_1+a_0+4.3\right )\cdot 27 +2\left (42.875a_3+12.25a_2+3.5a_1+a_0-32.5\right )\cdot 42.875\\ = & -3122.68 + 121.75 a_0 + 496.125 a_1 + 1470.44 a_2 + 5264.53 a_3\end{align*}

So, we get the system:
\begin{align*}& \ \ \ \ 89.8 + 10 a_0 + 7 a_1+ 52.5 a_2 + 121.75 a_3=0 \\ &-109.7 + 15 a_0 + 36.5 a_1 + 153.75 a_2 + 432.125 a_3=0 \\ &-414.85 + 52.5 a_0 + 121.75 a_1 + 496.125 a_2 + 1470.44 a_3=0 \\ &-3122.68 + 121.75 a_0 + 496.125 a_1 + 1470.44 a_2 + 5264.53 a_3=0\end{align*}

Then we get the solution: \begin{equation*}a_0\approx -21.6611, \ a_1\approx -7.08875, \ a_2\approx -2.0.6057, \ a_3\approx 2.33768\end{equation*}

The cubic polynomial that we are looking for is \begin{equation*}p(x)=2.33768x^3-2.0.6057x^2-7.08875x-21.6611 \end{equation*}
Doing the above in an other way I got an other result, but I don't know why and which is the correct one. (Wondering)

Using the least square method and the normal equation we get that the solution that we are looking for is the vector $\vec{a}$ such that $A \vec{a}=b \Rightarrow A^TA\vec{a}=A^Tb$.

So we get the following:
\begin{equation*}
\begin{bmatrix}
5 & 3.5 & 26.25 & 60.875 \\
3.5 & 26.25 & 60.875 & 248.0625 \\
26.25 & 60.875 & 248.0625 & 735.21875 \\
60.875 & 248.0625 & 735.21875 & 2632.265625
\end{bmatrix}
\begin{bmatrix}
a_0 \\
a_1 \\
a_2 \\
a_3 \\
\end{bmatrix}=
\begin{bmatrix}
-44.9 \\
186 \\
207.425 \\
1561.3375 \\
\end{bmatrix}
\end{equation*}

Solving this one we get the polynomial $$p(x)=-23.0087-12.2424x-2.7837x^2+3.0565x^3$$ This is not the same polynomial as the one that we get at the first method. And for the second polynomial the condition $p(0)=-20.1$ is not true. (Wondering)
 
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Hey mathmari!

I checked the solution $a=(A^T A)^{-1} A^T y$, and found the same solution that you did.
If I graph it, I get:
View attachment 8788
https://octave-online.net/
xx=[-2 -1 0 3 3.5]';
yy=[-33 -20 -20.1 -4.3 32.5]';
A=[ones(5,1) xx xx.^2 xx.^3];
ATA = A'*A
ATy = A'*yy
a = ATA\ATy
plot(xx,yy)
hold on
plot(xx, A*a)
That looks pretty close doesn't it, even though $p(0)$ is slightly off? (Wondering)

And yes, your solution with the derivatives set to zero should have the same result. (Worried)EDIT: Now I've also plotted it with the $a$ you found with the derivatives:
View attachment 8789
a_diff = [-21.6611, -7.08875, -2.06057, 2.33768]'
plot(xx, A*a_diff)

Hmm... that's not the same is it?
The first one does look better though.
Perhaps there is a mistake? (Wondering)EDIT 2:
If I calculate the residu $\|Aa-y\|$ in both cases, I get:
Code:
>> norm(A*a-yy)
ans =  5.2292
>> norm(A*a_diff-yy)
ans =  7.5340

In other words, the solution with the derivatives did not find the lowest possible residu.
It confirms that there must be a calculation mistake. (Worried)
 

Attachments

  • cubic_lsq.png
    cubic_lsq.png
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  • cubic_lsq_diff.png
    cubic_lsq_diff.png
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I checked my calculations again and I saw that I had a wrong sign. Now I get \begin{equation*}p(x)=3.05677x^3-2.78419x^2-12.2439x-23.0084 \end{equation*} which is approximately the same as the second one. Do we have have to get the exactly same polynomial or is it correct that we get approximately the same one? But what about the value of the polynomial at $x=0$ ? Shouldn't it be as the given value? (Wondering)
 
mathmari said:
I checked my calculations again and I saw that I had a wrong sign. Now I get \begin{equation*}p(x)=3.05677x^3-2.78419x^2-12.2439x-23.0084 \end{equation*} which is approximately the same as the second one. Do we have have to get the exactly same polynomial or is it correct that we get approximately the same one? But what about the value of the polynomial at $x=0$ ? Shouldn't it be as the given value?

Good!
The first 4 significant digits of each coefficient are the same.
I think it means that intermediate results of the numbers have been rounded to perhaps 5 or 6 significant digits.
The results should be exactly the same, but of cause they are sensitive to rounding.
Anyway, they are close enough that I believe that the calculations are correct now. (Thinking)And no, the value of polynomial is not expected to be the same as the given value at $x=0$.
It is an approximation after all.
We can only fit a cubic polynomial perfectly through 4 points.
Since 5 points were given, it is normal that every point is slightly off from the given value.
The squared sum of the differences is merely as low as possible. (Nerd)
 

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