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Say $\boldsymbol{\beta}$ is a random n-vector having the multivariate normal distribution with mean $\boldsymbol{b}$ and covariance matrix $\boldsymbol{S}$. And let $\boldsymbol{x}_1$ and $\boldsymbol{x}_2$ be two row vectors with n elements each. Then we know the distribution of $\frac{exp(\boldsymbol{x_1\beta})}{1+exp(\boldsymbol{x_1\beta})}$ and $\frac{exp(\boldsymbol{x_2\beta})}{1+exp(\boldsymbol{x_2\beta})}$. Then can we determine the joint distribution of these two random variables?

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Where does this question come from? –  Igor Rivin Dec 25 '11 at 18:10
    
what does "can we determine the joint distribution of these two random variables"? You can indeed find an ugly formula for it. –  Alekk Dec 25 '11 at 19:27

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up vote 2 down vote accepted

If $A$ is the matrix with rows $x_1$ and $x_2$, then $A \beta$ has a bivariate normal distribution with mean $A b$ and covariance matrix $A S A^T$. From that you can get the joint distribution of your two random variables.

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