Hi again, thanks for your answers on my last posting. I meanwhile have another question which you can hopefully help me with.
Here is the scenario: It is quite easy to calculate the probability p(X > Y), if I have two independent normally distributed variables X and Y. However, I currently don't know how to efficiently calculate the probability that one variable is the maximum, if there are more than two variables. To be concrete: X is normally distributed with mu_X and sigma_X Y_1...Y_n (n Variables) are normally distributed with mu_Y and sigma_Y mu_X > mu_Y all variables (X, Y1, ... Yn) are independent! How can I efficiently calculate the probability that x is the maximum in a realisation (x,y1, .... ,y) ? Well it cannot be calculated by multiplying p(X>Y1)*p(X>Y2)* .... *p(X>Yn) I currently calculate the probability that x is the maximum in a realisation by transforming the normal distributions to discrete distributions. This way I can numerically calculate the searched probability. But I guess there is a much better way to do this. Thanks! Stefan . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
