Category: Simulation

Fundamental Bayesian Samplers

Introduction The posterior probability distribution is the heart of Bayesian statistics and a fundamental tool for Bayesian parameter estimation. Naturally, how to infer and build these distributions is a widely examined topic, the scope of which cannot fit in one blog. We can, however, start to build a better understanding of sampling by examining three [...]

Repeating simulations from older versions of GAUSS

Introduction Starting in GAUSS version 12, a new suite of random number generators was introduced. GAUSS now contains several options of high quality and high-performance random number generators (RNG), such as: The Mersenne-Twister (MT-19937, SFMT-19937 and MT-2208). Pierre L'ECuyer's MRG32K3a. Niederreiter and Sobol quasi-random number generators. GAUSS version 11 and older used a linear congruential [...]

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