Description Usage Arguments Details Value Author(s) References See Also Examples

General linear congruential generators such as Park Miller sequence, generalized feedback shift register such as SF-Mersenne Twister algorithm and WELL generator; and a quasi random generator (pseudo random generators) and the Torus algorithm (quasi random generation).

1 2 3 4 5 6 | ```
WELL2test(n, dim = 1, order = 512, temper = FALSE, version = "a")
setSeed4WELL(seed)
doinitMT2002(seed, n, state)
doputRngWELL(order, version, state)
dogetRngWELL(order, version, state)
``` |

`n` |
number of observations. If length(n) > 1, the length is taken to be the required number. |

`dim` |
dimension of observations (must be <=100 000, default 1). |

`seed` |
a single value, interpreted as a positive integer for the seed. e.g. append your day, your month and your year of birth. |

`order` |
a positive integer for the order of the characteristic polynomial. see details |

`temper` |
a logical if you want to do a tempering stage. see details |

`version` |
a character either |

`state` |
the state as output of |

The currently available generator are given below.

**WELL generator:**-
The WELL (which stands for Well Equidistributed Long-period Linear) is in a sentence a generator with better equidistribution than Mersenne Twister algorithm but this gain of quality has to be paid by a slight higher cost of time. See Panneton et al. (2006) for details.

The

`order`

argument of`WELL`

generator is the order of the characteristic polynomial, which is denoted by*k*in Paneton F., L'Ecuyer P. and Matsumoto M. (2006). Possible values for`order`

are 512, 521, 607, 1024 where no tempering are needed (thus possible). Order can also be 800, 19937, 21071, 23209, 44497 where a tempering stage is possible through the`temper`

argument. Furthermore a possible 'b' version of WELL RNGs are possible for the following order 521, 607, 1024, 800, 19937, 23209 with the`version`

argument.All the C code for WELL generator used in this package is the code of P. L'Ecuyer (cf. http://www.iro.umontreal.ca/~lecuyer/), except some C code, we add, to

*interface*with R.

See the pdf vignette for details.

`WELL2test`

generates random variables in [0,1[. It returns a *n*x*dim* matrix, when `dim`

>1 otherwise a vector of length `n`

.

`setSeed4WELL`

set the seed of the `rngWELL`

package
(i.e. for the `WELL2test`

functions).

Christophe Dutang and Petr Savicky

Paneton F., L'Ecuyer P. and Matsumoto M. (2006), *Improved Long-Period Generators
Based on Linear Recurrences Modulo 2*, ACM Transactions on Mathematical Software. (preprint
available online)

`.Random.seed`

for what is done in R about random number generation.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ```
# (1) WELL generator
#
# 'basic' calls
# WELL512
WELL2test(10, order = 512)
# WELL1024
WELL2test(10, order = 1024)
# WELL19937
WELL2test(10, order = 19937)
# WELL44497
WELL2test(10, order = 44497)
# WELL19937 with tempering
WELL2test(10, order = 19937, temper = TRUE)
# WELL44497 with tempering
WELL2test(10, order = 44497, temper = TRUE)
# tempering vs no tempering
setSeed4WELL(08082008)
WELL2test(10, order =19937)
setSeed4WELL(08082008)
WELL2test(10, order =19937, temper=TRUE)
# (2) other tests
#
doinitMT2002(1, 10, 10)
``` |

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