Gaussian Ratio Distribution
When X and Y are independent and have a Gaussian distribution with zero mean the form of their ratio distribution is fairly simple: It is a Cauchy distribution. However, when the two distributions have non-zero means then the form for the distribution of the ratio is much more complicated. In 1969 David Hinkley found a form for this distribution. In the absence of correlation (cor(X,Y) = 0), the probability density function of the two normal variable X = N(μX, σX2) and Y = N(μY, σY2) ratio Z = X/Y is given by the following expression:
where
The above expression becomes even more complicated if the variables X and Y are correlated. It can also be shown that p(z) is a standard Cauchy distribution if μX = μY = 0, and σX = σY = 1. In such case b(z) = 0, and
If, or the more general Cauchy distribution is obtained
where ρ is the correlation coefficient between X and Y and
The complex distribution has also been expressed with Kummer's confluent hypergeometric function or the Hermite function.
Read more about this topic: Ratio Distribution
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