Universal Generators for Correlation Induction

Compared with algorithms specialized for a single distribution universal (also called automatic or black-box) algorithms for continuous distributions were relatively seldom discussed. But they have important advantages for the user: One algorithm coded and tested only once can do the same or even more than a whole library of standard routines. It is only necessary to have a program available that can evaluate the density of the distribution up to a multiplicative factor. In this paper we show that transformed density rejection is well suited to construct universal algorithms suitable for correlation induction which is important for variance reduction in simulation. (author's abstract)