Marsaglia Polar Method
The polar method (attributed to George Marsaglia, 1964) is a pseudo-random number sampling method for generating a pair of independent standard normal random variables. While it is superior to the Box–Muller transform, the Ziggurat algorithm is even more efficient.
Standard normal random variables are frequently used in computer science, computational statistics, and in particular, in applications of the Monte Carlo method.
The polar method works by choosing random points (x, y) in the square −1 < x < 1, −1 < y < 1 until
and then returning the required pair of normal random variables as
Read more about Marsaglia Polar Method: Theoretical Basis, History, Practical Considerations, Implementation
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