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Pseudocode is commonly used in textbooks and scientific publications related to computer science and numerical computation to describe algorithms in a way that is accessible to programmers regardless of their familiarity with specific programming languages.
Wichmann–Hill is a pseudorandom number generator proposed in 1982 by Brian Wichmann and David Hill. [1] It consists of three linear congruential generators with different prime moduli, each of which is used to produce a uniformly distributed number between 0 and 1. These are summed, modulo 1, to produce the result. [2]
The Mersenne Twister is a general-purpose pseudorandom number generator (PRNG) developed in 1997 by Makoto Matsumoto (松本 眞) and Takuji Nishimura (西村 拓士). [1] [2] Its name derives from the choice of a Mersenne prime as its period length.
PSeInt is designed to assist students who start in the construction of computer algorithms or programs. The pseudocode is usually used as the first contact to introduce basic concepts such as the use of control structures, expressions, variables, etc., without having to deal with the particularities of the syntax of a real language.
The maximum period of lagged Fibonacci generators depends on the binary operation .If addition or subtraction is used, the maximum period is (2 k − 1) × 2 M−1.If multiplication is used, the maximum period is (2 k − 1) × 2 M−3, or 1/4 of period of the additive case.
The following is pseudocode which combines Atkin's algorithms 3.1, 3.2, and 3.3 [1] by using a combined set s of all the numbers modulo 60 excluding those which are multiples of the prime numbers 2, 3, and 5, as per the algorithms, for a straightforward version of the algorithm that supports optional bit-packing of the wheel; although not specifically mentioned in the referenced paper, this ...
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It can be shown that if is a pseudo-random number generator for the uniform distribution on (,) and if is the CDF of some given probability distribution , then is a pseudo-random number generator for , where : (,) is the percentile of , i.e. ():= {: ()}. Intuitively, an arbitrary distribution can be simulated from a simulation of the standard ...