Recent content by alondo

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    Graduate Multivariate Normal conditional tail Expextation

    It was not a mistake, but the bi-variate case: E[X1|X2 > z] still holds when X2 is correlated to X1.
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    Graduate Multivariate Normal conditional tail Expextation

    Hi, Thanks for your detailed answer. So you don't think there is a close solution like in the bi-variate case?: http://en.wikipedia.org/wiki/Multivariate_normal_distribution (look at around the middle-end of the page) Alon
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    Graduate Multivariate Normal conditional tail Expextation

    Hi and thanks for your reply, The variables are dependent, and the covariance matrix can be calculated. However, I am not sure how to deal with the multiple conditions of the expectation: E(x1|X>K)=E(x1|x1>k1,x2,k2,...,x_n>k_n) Thanks, and hope you can help. Alon
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    Graduate Multivariate Normal conditional tail Expextation

    Hi all, I need help regarding the following expression: E(x1|X>K) where: x1 is a one dimension normal rv X is multivariate normal rv with n components: x1, x2,..., x_n K is a n dimension constant vector with n components: k1,k2,...,k_n X>K <==> x1>k1,x2>k2,...,x_n>k_n I know there is...