This function computes the Q function by integrating the Normal distribution.
It takes one paramter and calculates the right tail probablity.
x would have the value of .5
For an arbitrary Gaussian distribution with mean, mu, and variance, sigma^2, then the function is passed this form.
Ex. Say you have a distribution of G(3,4). mu = 3, and sigma = 2. You want to calculate the right tail probability that it will be greater than 3.5. The function call would look like
This is not the most efficient way of calculating this. I wrote this because I didn't have the proper toolbox. If you have the toolbox its just QFunc.
This function was needed for a Satellite COmmunictation class. I had to have Q(x), not erf(x). I tested it today on Matlab R2009a and it works. Thanks Mr. Felty!
why not simply use built-in ERF function?
function answer = q(x)
answer = 1/2*(1-erf(x/sqrt(2)));
Thanks Timothy and TJ
The Q function is related to the complementary error function, which is available in Matlab as erfc, so qx = erfc(x/sqrt(2))/2 yields Q(x) without explicit integration.
Sorry about that. It calculates the tail end probability of a Gaussain distribution. It calculates the area from a point x on the distribution to infinity, giving the probability.
Probably it would be nice to have a definition of the Q function. Some other submissions suffer from the same problem: the authors are so inmersed in their own field that it is difficult to an outsider to take advantage of the submissions.
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