Stochastic Simulation in Java

Random Number Generators. More...
Classes  
class  AntitheticStream 
This container class allows the user to force any RandomStream to return antithetic variates. More...  
class  BakerTransformedStream 
This container class permits one to apply the baker’s transformation to the output of any RandomStream. More...  
class  BasicRandomStreamFactory 
Represents a basic random stream factory that can constructs new instances of a given RandomStream implementation via the newInstance method. More...  
interface  CloneableRandomStream 
CloneableRandomStream extends RandomStream and Cloneable. More...  
class  F2NL607 
Implements the RandomStream interface by using as a backbone generator the combination of the WELL607 proposed in [188], [187] (and implemented in WELL607 ) with a nonlinear generator. More...  
class  F2wPoly 
class  GenF2w32 
Implements the RandomStream interface via inheritance from RandomStreamBase. More...  
class  LFSR113 
Extends RandomStreamBase using a composite linear feedback shift register (LFSR) (or Tausworthe) RNG as defined in [142], [218] . More...  
class  LFSR258 
Extends RandomStreamBase using a 64bit composite linear feedback shift register (LFSR) (or Tausworthe) RNG as defined in [142], [218] . More...  
class  MRG31k3p 
Extends the abstract class RandomStreamBase, thus implementing the RandomStream interface indirectly. More...  
class  MRG32k3a 
Extends the abstract class RandomStreamBase by using as a backbone (or main) generator the combined multiple recursive generator (CMRG) MRG32k3a proposed by L’Ecuyer [143] , implemented in 64bit floatingpoint arithmetic. More...  
class  MRG32k3aL 
The same generator as MRG32k3a, except here it is implemented with type long instead of double . More...  
class  MT19937 
Implements the RandomStream interface via inheritance from RandomStreamBase. More...  
class  RandMrg 
USE MRG32k3a INSTEAD of this class. More...  
class  RandomPermutation 
Provides methods to randomly shuffle arrays or lists using a random stream. More...  
interface  RandomStream 
This interface defines the basic structures to handle multiple streams of uniform (pseudo)random numbers and convenient tools to move around within and across these streams. More...  
class  RandomStreamBase 
This class provides a convenient foundation on which RNGs can be built. More...  
interface  RandomStreamFactory 
Represents a random stream factory capable of constructing instances of a given type of random stream by invoking the newInstance method each time a new random stream is needed, instead of invoking directly the specific constructor of the desired type. More...  
class  RandomStreamInstantiationException 
This exception is thrown when a random stream factory cannot instantiate a stream on a call to its umontreal.ssj.rng.RandomStreamFactory.newInstance method. More...  
class  RandomStreamManager 
Manages a list of random streams for more convenient synchronization. More...  
class  RandomStreamWithCache 
This class represents a random stream whose uniforms are cached for more efficiency when using common random numbers. More...  
class  RandRijndael 
Implements a RNG using the Rijndael block cipher algorithm (AES) with key and block lengths of 128 bits. More...  
class  Rijndael_Algorithm 
Rijndael –pronounced Reindaal– is a variable blocksize (128, 192 and 256bit), variable keysize (128, 192 and 256bit) symmetric cipher. More...  
class  Rijndael_Properties 
This class acts as a central repository for an algorithm specific properties. More...  
class  TruncatedRandomStream 
Represents a container random stream generating numbers in an interval \((a,b)\) instead of in \((0,1)\), where \(0\le a < b \le1\), by using the contained stream. More...  
class  WELL1024 
Implements the RandomStream interface via inheritance from RandomStreamBase. More...  
class  WELL512 
This class implements the RandomStream interface via inheritance from RandomStreamBase. More...  
class  WELL607 
This class implements the RandomStream interface via inheritance from RandomStreamBase. More...  
class  WELL607base 
Random Number Generators.
This package offers the basic facilities for generating uniform random numbers. It provides an interface called umontreal.ssj.rng.RandomStream and some implementations of that interface. The interface specifies that each stream of random numbers is partitioned into multiple substreams and that methods are available to jump between the substreams, as discussed in [120], [118], [132], [151], [139]. For an example of how to use these streams properly, see InventoryCRN
in the set of example programs.
Each implementation uses a specific backbone uniform random number generator (RNG), whose period length is typically partitioned into very long nonoverlapping segments to provide the streams and substreams. A stream can generate uniform variates (real numbers) over the interval (0,1), uniform integers over a given range of values \(\{i,…,j\}\), and arrays of these.
The generators provided here have various speeds and period lengths. umontreal.ssj.rng.MRG32k3a is the one that has been most extensively tested, but it is not among the fastest. The umontreal.ssj.rng.LFSR113, umontreal.ssj.rng.GenF2w32, umontreal.ssj.rng.MT19937, and the WELL
generators produce sequences of bits that obey a linear recurrence, so they eventually fail statistical tests that measure the linear complexity of these bits sequences. But this can affect only very special types of applications.
We recommend primarily umontreal.ssj.rng.MRG31k3p, umontreal.ssj.rng.MRG32k3a, and umontreal.ssj.rng.LFSR113. Note that all the generators provided currently in SSJ were originally designed for 32bit computers.
For each base generator, the following tables give the approximate period length (period), the CPU time (in seconds) to generate \(10^9\) \(U(0,1)\) random numbers (gen. time), and the CPU time to jump ahead \(10^6\) times to the next substream (jump time). The following timings were on a 2100 MHz 32bit AMD Athlon XP 2800+ computer running Linux, with the JDK 1.4.2.
RNG  period  gen. time  jump time 
LFSR113  \(2^{113}\)  51  0.08 
WELL512  \(2^{512}\)  55  372 
WELL1024  \(2^{1024}\)  55  1450 
MT19937  \(2^{19937}\)  56  60 
WELL607  \(2^{607}\)  61  523 
GenF2w32  \(2^{800}\)  62  937 
MRG31k3p  \(2^{185}\)  66  1.8 
MRG32k3a  \(2^{191}\)  109  2.3 
F2NL607  \(2^{637}\)  125  523 
RandRijndael  \(2^{130}\)  260  0.9 
The following timings are on a 2400 MHz 64bit AMD Athlon 64 Processor 4000+ computer running Linux, with the JDK 1.5.0.
RNG  period  gen. time  jump time 
LFSR113  \(2^{113}\)  31  0.08 
WELL607  \(2^{607}\)  33  329 
WELL512  \(2^{512}\)  33  234 
WELL1024  \(2^{1024}\)  34  917 
LFSR258  \(2^{258}\)  35  0.18 
MT19937  \(2^{19937}\)  36  46 
GenF2w32  \(2^{800}\)  43  556 
MRG31k3p  \(2^{185}\)  51  0.89 
F2NL607  \(2^{637}\)  65  329 
MRG32k3a  \(2^{191}\)  70  1.1 
RandRijndael  \(2^{130}\)  127  0.6 
Other tools included in this package permit one to manage and synchronize several streams simultaneously ( umontreal.ssj.rng.RandomStreamManager ), to create random stream factories for a given type of stream ( umontreal.ssj.rng.BasicRandomStreamFactory ), and to apply automatic transformations to the output of a given stream ( umontreal.ssj.rng.AntitheticStream and umontreal.ssj.rng.BakerTransformedStream ).
For further details about uniform RNGs, we refer the reader to [110], [145], [148], [150], [151], [152] .