SUSE Package Hub 15 one-click install Install ghc-rvar NOTE: This one-click installation requires that the SUSE Package Hub extension to already be enabled. See http://packagehub.suse.com/how-to-use/ for information on enabling the Package Hub extension If the extension is not enabled, this installation will fail while trying to enable an invalid repo. This package might depend on packages from SUSE Linux Enterprise modules. If those modules are not enabled, a package dependency error will be encountered. SUSE-PackageHub-15-Standard-Pool Package Hub 15 Dummy repo - this will fail ghc-rvar Random Variables Random number generation based on modeling random variables by an abstract type ('RVar') which can be composed and manipulated monadically and sampled in either monadic or "pure" styles. The primary purpose of this library is to support defining and sampling a wide variety of high quality random variables. Quality is prioritized over speed, but performance is an important goal too. In my testing, I have found it capable of speed comparable to other Haskell libraries, but still a fair bit slower than straight C implementations of the same algorithms. Changes in 0.2.0.1: Version bump for transformers dependency. SUSE Package Hub 15 one-click install Install ghc-rvar NOTE: This one-click installation requires that the SUSE Package Hub extension to already be enabled. See http://packagehub.suse.com/how-to-use/ for information on enabling the Package Hub extension If the extension is not enabled, this installation will fail while trying to enable an invalid repo. This package might depend on packages from SUSE Linux Enterprise modules. If those modules are not enabled, a package dependency error will be encountered. SUSE-PackageHub-15-Standard-Pool Package Hub 15 Dummy repo - this will fail ghc-rvar Random Variables Random number generation based on modeling random variables by an abstract type ('RVar') which can be composed and manipulated monadically and sampled in either monadic or "pure" styles. The primary purpose of this library is to support defining and sampling a wide variety of high quality random variables. Quality is prioritized over speed, but performance is an important goal too. In my testing, I have found it capable of speed comparable to other Haskell libraries, but still a fair bit slower than straight C implementations of the same algorithms. Changes in 0.2.0.1: Version bump for transformers dependency.