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| author | Gertjan van den Burg <gertjanvandenburg@gmail.com> | 2015-07-30 18:48:58 +0200 |
|---|---|---|
| committer | Gertjan van den Burg <gertjanvandenburg@gmail.com> | 2015-07-30 18:48:58 +0200 |
| commit | 1c2dcd1125d4a542a7b4b291e8de1f3b3cdc86a0 (patch) | |
| tree | 69f2ecfefa8630655cd09433973730a0a75f0a83 /README.md | |
| parent | fix typos in README (diff) | |
| download | SyncRNG-1c2dcd1125d4a542a7b4b291e8de1f3b3cdc86a0.tar.gz SyncRNG-1c2dcd1125d4a542a7b4b291e8de1f3b3cdc86a0.zip | |
By passing numbers between R and C as doubles we can avoid the limitations of the R integer type. This allows us to create a uniform RNG.
Diffstat (limited to 'README.md')
| -rw-r--r-- | README.md | 13 |
1 files changed, 3 insertions, 10 deletions
@@ -52,18 +52,11 @@ You'll notice that the random numbers are indeed the same. Notes ----- -Since R is not capable of reliably handling integers larger than `2^32 - 1`, -the random numbers are internally capped at this value (using a bitwise and -with `0x7FFFFFF`), this influences the quality of the random numbers. The -random numbers are no longer uniformly distributed on `[0, 2^32 -1]`. For the -intended use of SyncRNG this is not a problem, but it is a compromise worth -considering when using SyncRNG. SyncRNG should definitely not be used for any -cryptographic purposes. +The random numbers are uniformly distributed on `[0, 2^32 - 1]`. TODO ---- -Future versions may include a random number generator that does not need -capping, and is uniform. It may also provide easier system-wide installation -through an R package and a Python module. +It may be easier to provide system-wide installation through an R package and +a Python module. |