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Changes in 0.4.1:
* Add applicative instances to GSL's MC and MCT.
* Add many distributions: beta, logistic, Pareto, Weibull, gamma,
multinomial and Dirichlet distributions are now available.
Changes in 0.3.1:
* Change upper bound on vector dependency.
Changes in 0.3:
* Add strict versions of sampleSubset, sampleIntSubset, and shuffleInt.
* Port to vector-0.6.0.
* Add Exponential and Levy alpha-Stable distributions.
* Add Summary.Bool for indicators.
* Move Summary to Data.Summary
* Introduce `repeatMC`, which produces an infinite (lazy) stream of values, and
`replicateMC`, which produces a lazy list of specified length.
* Remove `repeatMC/repeatMCWith`.
* Build fix for 6.8.2 from Robert Gunst.
* The function `sample`, `sampleWithWeights`, `sampleSubset`, and
`shuffle` no longer require that you explicitly pass in the length.
* The pure RNG is now a newtype, so you can't use the functions from
GLS.Random.Gen on it anymore.
* The internals of the monad have been cleaned up. IO is used internally
instead of `seq` calls and `unsafePerformIO` everywhere. This results in
a modest performance boost.
Changes in 0.2:
* More general type class, MonadMC, which allows all the functions to work
in both MC and MCT monads.
* Functions to sample from discrete distributions.
* Functions to sample subsets