RT Journal Article T1 Gamma pseudo random number generators A1 Almaraz Luengo, Elena Salome AB Communication, among others. Throughout history, different algorithms have been developed for the generation of such values and advances in computing have made them increasingly faster and more efficient from a computational point of view. These advances also allow the generation of higher-quality inputs (from the point of view of randomness and uniformity) for these algorithms that are easily tested by different statistical batteries such as NIST, Dieharder, or TestU01 among others. This article describes the existing algorithms for the generation of (independent and identically distributed—i.i.d.) Gamma distribution values as well as the theoretical and mathematical foundations that support their validity. PB Association for Computing Machinery (ACM) SN 0360-0300 YR 2022 FD 2022 LK https://hdl.handle.net/20.500.14352/96841 UL https://hdl.handle.net/20.500.14352/96841 LA eng NO Elena Almaraz Luengo. 2023. Gamma Pseudo Random Number Generators. ACM Comput. Surv. 55, 4 (May 2023), 1–33. https://doi.org/10.1145/3527157 DS Docta Complutense RD 11 abr 2025