FAST PSEUDORANDOM GENERATORS FOR NORMAL AND EXPONENTIAL VARIATES

Fast algorithms for generating pseudorandom numbers from the unit-norm al and unit-exponential distributions are described. The methods are u nusual in that they do not rely on a source of uniform random numbers, but generate the target distributions directly by using their maximal -entropy properties. The algorithms are fast. The normal generator is faster than the commonly used Unix library uniform generator ''random' ' when the latter is used to yield real values. Their statistical prop erties seem satisfactory, but only a limited suite of tests has been c onducted. They are written in C and as written assume 32-bit integer a rithmetic. The code is publicly available as C source and can easily b e adopted for longer word lengths and/or vector processing.