What I want is the uncertainty in the coefficients

AI Thread Summary
The discussion centers on calculating the uncertainty in the coefficients of an 8th order polynomial fitted to data from an ion engine experiment. The user initially struggles with the invertibility of the design matrix, realizing that while the matrix A is not square, the product (A^T A) is square and invertible. After some troubleshooting, the user successfully computes the covariance matrix and the associated uncertainties using the square root of the diagonals of (A^T A)^{-1}. The conversation highlights the importance of understanding matrix properties in statistical analysis. Ultimately, the user resolves their issue and expresses relief at finding the solution.
Winzer
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Homework Statement


I was given a set of data from a Ion engine experiment. I fitted the data with an 8th order polynomial that seems pretty reasonable. What I want is the uncertainty in the coefficients.
One way I read was through the design matrix.

Homework Equations


C_{ij}=(A^T A)^{-1}

The Attempt at a Solution


The square root of the diagonals give the uncertainties. But my matrix in not invertible since its not square.
What am I missing?
 
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Winzer said:

Homework Statement


I was given a set of data from a Ion engine experiment. I fitted the data with an 8th order polynomial that seems pretty reasonable. What I want is the uncertainty in the coefficients.
One way I read was through the design matrix.

Homework Equations


C_{ij}=(A^T A)^{-1}


The Attempt at a Solution


The square root of the diagonals give the uncertainties. But my matrix in not invertible since its not square.
What am I missing?

The matrix A may not be square, but

(A^T A)

is square, so it's invertible.
 
The Electrician said:
The matrix A may not be square, but

(A^T A)

is square, so it's invertible.
Thank you. Yes it turns out square but the inverse gives me problems.
Maybe I am using the command wrong.
Here are the results of a test.

I threw in .1 just for error sake. My model is a+bx+cx^2. The uncertainties are suppose to be given by the square root of the diagonals of
(A^T A)^{-1} A being the design matrix.
 

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Never mind I got it.
I was able to find the covariance matrix and the associated uncertainties. I feel stupid.
 
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