Is the determinant a linear operation?

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The discussion centers on whether the determinant is a linear operation, specifically questioning if the expectation of the determinant equals the determinant of the expectation. It concludes that this is not the case, as demonstrated by examples where the determinant of a matrix and its expected value diverge significantly. The conversation further explores the inequality involving logarithms of determinants and expectations, ultimately showing that the expected logarithm of the determinant does not equate to the logarithm of the determinant of the expected matrix. The example provided illustrates that while the expected log determinant can yield a finite value, the log determinant of the expected matrix can lead to negative infinity. Thus, the determinant does not exhibit linearity in the context of expectation.
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Is the determinant a linear operation? I mean can we say that:

\mathbb{E}[\text{det}]=\text{det}[\mathbb{E}]

where E is the expectation operator?
 
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First impression says no, but I'm testing it out now, I might be wrong.
 
No, it's not. For instance, det(aM) = andet(M). And det(M+N) doesn't have any simple relationship to det(M) and det(N). (See, for instance, http://en.wikipedia.org/wiki/Matrix_determinant_lemma" .)
 
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Ok, now we have this inequality:

\mathbb{E}\left[\log(X)\right]\leq\log\left(\mathbb{E}[X]\right)

Can we say in the same manner that:

\mathbb{E}\left[\log\left(\text{det}\left\{H\right\}\right)\right]\leq\log\left(\text{det}\left\{\mathbb{E}\left[H\right]\right\}\right)
 
S_David said:
Ok, now we have this inequality:

\mathbb{E}\left[\log(X)\right]\leq\log\left(\mathbb{E}[X]\right)

Can we say in the same manner that:

\mathbb{E}\left[\log\left(\text{det}\left\{H\right\}\right)\right]\leq\log\left(\text{det}\left\{\mathbb{E}\left[H\right]\right\}\right)
Nope. Suppose H=((1 0), (0 1)) with 50% probability and ((-1 0), (0 -1)) with 50% probability. Both of those have determinant 1, so E[log det H] = 0. But E[H] = ((0 0), (0, 0)), with determinant 0, so log det E[H] = -infinity.
 
pmsrw3 said:
Nope. Suppose H=((1 0), (0 1)) with 50% probability and ((-1 0), (0 -1)) with 50% probability. Both of those have determinant 1, so E[log det H] = 0. But E[H] = ((0 0), (0, 0)), with determinant 0, so log det E[H] = -infinity.

Ok, I see. Thanks a lot
 
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