What is the Geometric Approach to Proving Least Squares Approximation?

In summary, the problem asks for a geometric solution to a system that has more unknowns than equations. A possible solution is found using a bisecting plane and a geometric approach.
  • #1
Samuel Williams
20
3
Member warned about not using the HW template


My apologies for having to post in an image, my latex skills are not good enough for the question at hand :(

a) There is no solution since the system has more unknowns than equations (the equations are equal giving 1=2 which does not make sense).

b) I get a solution of \begin{bmatrix}1 \\1 \\ 3/2 \end{bmatrix}
for u.

c) I am not sure how to prove this directly, since there are no values for x,y or z.
 
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  • #2
First off, I do not see the picture for the problem, just the solution. Second, you should use the homework template in this forum.
 
  • #3
Samuel Williams said:


My apologies for having to post in an image, my latex skills are not good enough for the question at hand :(

a) There is no solution since the system has more unknowns than equations (the equations are equal giving 1=2 which does not make sense).

b) I get a solution of \begin{bmatrix}1 \\1 \\ 3/2 \end{bmatrix}
for u.

c) I am not sure how to prove this directly, since there are no values for x,y or z.
If the problem is not very complicated to state, just type it out in plain text. LaTeX is great, but don't let not knowing it stand in your way.
 
  • #4
Again, my apologies. It seems that I accidentally deleted the image.
So these are the questions
O6gHNRY.jpg

I did (a) and (b) as mentioned above and there are no relevant formulae or theorems that I am aware of for part (c).
 
  • #5
Right. For part b, anything that lands you at x - y + z = 3/2 is correct.
For part c, you are asked to show that any other choice for x, y, z such that x-y+z is not equal to 3/2, (x-y+z - 1)^2 + (x-y+z-2)^2 > (3/2 - 1)^2 + (3/2-2)^2 and equal only when x-y+z = 3/2.
There are plenty of methods to attack the problem, but you should be able to make a good argument without referring to formulae or theorems.
 
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  • #6
Samuel Williams said:
Again, my apologies. It seems that I accidentally deleted the image.
So these are the questions
O6gHNRY.jpg
I did (a) and (b) as mentioned above and there are no relevant formulae or theorems that I am aware of for part (c).

For (c), Least Squares is supposed to minimize the norm as defined. I think it minimizes the L^2 -norm. Still, you have a reference there for SG section 12.6. Did you check it out?
 
  • #7
RUber said:
Right. For part b, anything that lands you at x - y + z = 3/2 is correct.
For part c, you are asked to show that any other choice for x, y, z such that x-y+z is not equal to 3/2, (x-y+z - 1)^2 + (x-y+z-2)^2 > (3/2 - 1)^2 + (3/2-2)^2 and equal only when x-y+z = 3/2.
There are plenty of methods to attack the problem, but you should be able to make a good argument without referring to formulae or theorems.

Thanks, I managed to find a solution to the problem with your explanation to the question.
 
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  • #8
Nice geometric approach, RUBER, recognizing that the "bisecting" plane is in the solution set, much simpler than anything I had in mind.
 
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What is Least Squares Approximation?

Least Squares Approximation is a mathematical method used to find the best fit for a set of data points on a graph. It minimizes the sum of the squared distances between the data points and the line of best fit.

When is Least Squares Approximation used?

Least Squares Approximation is commonly used in data analysis and regression analysis to find a trend line that best represents the relationship between two variables. It is also used in curve fitting to find the best fit for a set of data points.

How does Least Squares Approximation work?

Least Squares Approximation works by minimizing the sum of the squared distances between the data points and the line of best fit. This is achieved by finding the slope and y-intercept of the line of best fit that minimizes this sum.

What are the advantages of using Least Squares Approximation?

One of the main advantages of Least Squares Approximation is that it is a simple and efficient method for finding the best fit for a set of data points. It also allows for the incorporation of measurement errors and can handle both linear and non-linear relationships between variables.

What are the limitations of Least Squares Approximation?

While Least Squares Approximation is a useful method, it does have some limitations. It assumes that the data points are normally distributed and that there is a linear relationship between the variables. It also does not take into account the influence of outliers on the line of best fit.

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