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2

I guess that UNR stands for something like “unit normal” distribution, better known as the standard normal distribution. The algorithm gives a pretty decent sampling of that. Note that its range (for V) is restricted to the interval [-4.23, 4.23] but more than 99.998% of all expected values would be in that range for a standard normal variable. As others ...


14

The short answer is that as a random number generator it's very poor algorithm, but on the other hand, the way it is used to generate random numbers with certain properties might be adequate for the task it was needed, so how good it is depends what you use it for. The updated new function called UNR has something to do with generating uniformly distributed ...


3

RND computes the inverse of the cumulative Gaussian distribution with mean 0 and standard deviation 1 (see, e.g., here). In other words, given a uniformly distributed random number in (0,1), it return a normally distributed random number. The actual RNG must be elsewhere.


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