Find the least squares approximation

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Homework Help Overview

The problem involves finding the least squares approximations for constants a and b in the context of a given relationship between data points. The relationship is specified as y = ax + b/x, and the goal is to minimize the sum of squares of the differences between observed and predicted values.

Discussion Character

  • Exploratory, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the formulation of the least squares problem, including the expression for the sum of squares S. There are attempts to clarify the relationship and confirm the correct setup for minimization.

Discussion Status

Some participants have offered insights into the formulation of the problem and the approach to minimize the sum of squares. There is ongoing exploration of the necessary steps to find the values of a and b, with no explicit consensus reached yet.

Contextual Notes

There is a lack of clarity regarding the specific nature of the data points and any additional constraints that may apply to the problem. Participants are working with the assumption that the relationship provided is correct for the context of the least squares approximation.

hsong9
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Homework Statement


Suppose a set of N data points {(xk,yk)}Nk=1 appears to satisfy the relationship for some constants a and b. Find the least squares approximations for a and b.


Homework Equations





The Attempt at a Solution


I really have no idea about this problem.
 
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You don't say what the relationship is, but let's say it's some function that we'll call y=f(x,a,b). The object of a least squares fit is to find a and b such that the sum of squares

S = \sum_{k-1}^N (y_k - f(x_k,a,b))^2

is minimized.
 
Thanks!
the relationship is y = ax + b/x.
Thus, S = Sigma ( y_k - (ax + b/x))^2, right?
and that's it?
 
hsong9 said:
Thanks!
the relationship is y = ax + b/x.
Thus, S = Sigma ( y_k - (ax + b/x))^2, right?
and that's it?

S = Sigma ( y_k - (a x_k + b/x_k))^2

and you must minimize this as a function of a and b.
 
Thanks!
So, to minimize S, set partial derivative for a and b equals to zero.
right?
Thanks again.
 

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