Existence and Uniqueness of a Linear Least Squares Solution

In summary, the conversation discusses the topic of linear least squares and finding a solution for the linear least squares problem. The concept of minimizing the error in y = a + bx is mentioned, and the suggestion is made to start with the sum of squares and minimize it with respect to a and b. The person also mentions missing a lecture and needing help with the topic.
  • #1
scotchtapeman
1
0
I'm studying for my numerical analysis final on tuesday, and I know this is going to be one of the problems, so any help is greatly appreciated.

Homework Statement


State and prove existence and uniqueness for the solution of the linear least squares problem.

Homework Equations


[itex]y \approx x B[/itex]
[itex]x' x B = x' y[/itex]

The Attempt at a Solution


linear least squares finds B such that [itex]\| y - x B \|[/itex] is minimized.

Since this is linear least squares, [itex]y = B_0 + B_1 x[/itex]

[itex]r_i = y_i - (B_0 + B_1 x_i)[/itex]
For [itex]1 \le i \le n, \delta r_i / \delta x_i = 0[/itex]
Then [itex](\delta y_i / \delta x_i) - B_1 = 0[/itex]

I missed this lecture and I can't find much help online, so I could be headed in the wrong direction. Thanks!
 
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  • #2
so say you want to find a,b such that it minimises the least square error in y = a + bx

start with the sum of the squares, to characterise the error for given a and b, then minimise w.r.t. a,b and you should be most of the way there
 

1. What is the meaning of "existence and uniqueness" in relation to a linear least squares solution?

The existence and uniqueness of a linear least squares solution refers to the fact that there is one and only one solution to a system of linear equations that minimizes the sum of the squared errors. This solution is unique and exists regardless of the number of variables in the system.

2. How is the existence and uniqueness of a linear least squares solution proven?

The existence and uniqueness of a linear least squares solution can be proven mathematically using linear algebra and matrix operations. It involves showing that the system of equations has a unique solution and that it is the only solution that minimizes the sum of squared errors.

3. What are the implications of a system having no unique solution?

If a system does not have a unique solution, it means that there are multiple solutions that could minimize the sum of squared errors. This could lead to ambiguity and uncertainty in the data analysis, making it difficult to draw definitive conclusions.

4. How does the number of data points affect the existence and uniqueness of a linear least squares solution?

The number of data points does not affect the existence and uniqueness of a linear least squares solution. As long as there are more data points than variables in the system, there will be a unique solution that minimizes the sum of squared errors.

5. Can the existence and uniqueness of a linear least squares solution be guaranteed in all cases?

No, the existence and uniqueness of a linear least squares solution cannot be guaranteed in all cases. There are certain cases, such as when the data points are collinear, that do not have a unique solution. It is important to carefully analyze the data and consider any potential limitations before applying linear least squares methods.

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