Random variate generation for exponentially and polynomially tilted stable distributions
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Generating random numbers from a distribution specified by its Laplace transform
Statistics and Computing
Efficiently sampling nested Archimedean copulas
Computational Statistics & Data Analysis
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Several algorithms for sampling exponentially tilted positive stable distributions have recently been suggested. Three of them are known as exact methods, that is, neither do they rely on approximations nor on numerically critical procedures. One of these algorithms is outperformed by another one uniformly over all parameters. The remaining two algorithms are based on different ideas and both have their advantages. After a brief overview of sampling algorithms for exponentially tilted positive stable distributions, the two algorithms are compared. A rule is derived when to apply which for sampling these distributions.