An Improved Algorithm for Generation of Truncated Normal Distributed Random Numbers - Sahakyan, Vahe V. (Mathematical Problems of Computer Science, 2021)
In this paper we discuss the computational problems of random numbers generation distributed by truncated normal distribution. It is shown that the standard methods and libraries have a limit for truncation point caused by the limit on the smallest number representable by double precision format. Theoretically the problems arise starting from the truncation point ≈ 40, but in practical calculations the limit is lower, starting from ≈ 8.5. An improved method is represented, based on the combination of two approximation algorithms, which with the represented coefficients has 4.5 times more coverage interval than the standard methods.