Determinant of enlarged Correlation Matrix

In summary, the conversation discusses the determinant of an "enlarged" correlation matrix with a special structure. The problem is to find the determinant for dimension n+1 given the determinant for dimension n. The formula for the n-th determinant is also mentioned. One member asks if there are results for determinants of partitioned or tensor product matrices.
  • #1
LocalVol
1
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Determinant of "enlarged" Correlation Matrix

Hi guys,

I am not a physicist but saw that you guys are actively discussing math problems in this forum. I have the following problem that I've been fighting with for some time now: I have a n-dimensional (n >= 3) correlation matrix with the following special structure

[itex]C(n, \rho, x) = \left( \begin{array}{c c c c c} 1 & \rho & x & \dots & \rho\\ \rho & 1 & \rho & \dots & \rho\\ x & \rho & 1 & \dots & \rho\\ \vdots & \vdots & \vdots & \ddots & \vdots\\ \rho & \rho & \rho & \dots & 1 \end{array} \right). [/itex]

I.e. all off-diagonal entries are equal to [itex]\rho[/itex] except for the correlation pair (1, 3). Here is my problem: Let's say I know that the determinant for dimension n is given by [itex]\psi(n)[/itex]. What is the determinant for dimension n + 1? I played around with Mathematica and found that for n = 3

[itex]\psi(3) = 1 - x^2 - 2 \rho^2 + 2 x \rho^2[/itex]

(this was the easy part) and for n >= 4, we have the relationship

[itex]\psi(n) = (\rho - 1) \left( -\psi(n - 1) + (-1)^n (x - 1) (\rho - 1)^{n - 4} \left( \rho (1 + x) - 2 \rho^2 \right) \right)[/itex]

(this is my problem - how to show this?). Equivalently, we can directly state the formula for the n-th determinant (n >= 3) as

[itex]\psi(n) = (-1)^n (x - 1) (\rho - 1)^{n - 3} \left( 1 + x + (n - 3) \rho (1 + x) - 2 (n - 2) \rho^2 \right)[/itex]

but I have no clue of how to get there. Note that by increasing the dimension by one, we basically set

[itex]C(n, \rho, x) = \left( \begin{array}{c c} C(n - 1, \rho, x) & \rho 1_{\{ (n - 1) \times 1 \}}\\ \rho 1_{\{ 1 \times (n - 1) \}} & 1 \end{array} \right) [/itex]

Any help is appreciated!
 
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  • #2


Hey LocalVol.

One question I have for you is are there results for determinants given a partitioned matrix or a matrix which is a tensor product of existing matrices?

In other words if your final matrix is a tensor product of matrices A X B then is there a result that looks at the determinant of A X B in terms of det(A) and det(B)?

I don't know enough linear algebra to know if such a result exists.
 

1. What is a determinant of an enlarged correlation matrix?

The determinant of an enlarged correlation matrix is a numerical value that represents the size and orientation of the matrix. It is calculated by multiplying the values along the main diagonal of the matrix and subtracting the product of the values along the opposite diagonal.

2. How is the determinant of an enlarged correlation matrix used in statistical analysis?

The determinant of an enlarged correlation matrix is used in statistical analysis to determine the strength of the relationship between variables in a dataset. A larger determinant indicates a stronger overall correlation, while a smaller determinant suggests a weaker correlation or no correlation at all.

3. Can the determinant of an enlarged correlation matrix be negative?

No, the determinant of an enlarged correlation matrix cannot be negative. It is always a positive value, as it is calculated by multiplying positive values along the main diagonal and subtracting positive values along the opposite diagonal.

4. What is the significance of a determinant of an enlarged correlation matrix equal to zero?

If the determinant of an enlarged correlation matrix is equal to zero, it means that there is a perfect linear relationship between two or more variables in the dataset. This is called multicollinearity and can affect the accuracy and reliability of statistical analyses.

5. How does the size of a correlation matrix affect its determinant?

The size of a correlation matrix does not affect its determinant. The determinant is only dependent on the values within the matrix and not its dimensions. However, larger matrices may be more difficult to interpret and analyze due to the increased number of variables and correlations.

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