| lcg {fBasics} | R Documentation |
Functions to generate portable random innovations.
The functions run under R and S-Plus and generate
the same sequence of random numbers. Supported
are uniform, normal and Student-t distributed
random numbers.
The functions are:
set.lcgseed | Set initial random seed, |
get.lcgseed | Get the current valus of the random seed, |
runif.lcg | Uniform linear congruational generator, |
rnorm.lcg | Normal linear congruational generator, |
rt.lcg | Student-t linear congruential generator. |
set.lcgseed(seed = 4711) get.lcgseed() runif.lcg(n, min = 0, max = 1) rnorm.lcg(n, mean = 0, sd = 1) rt.lcg(n, df)
df |
number of degrees of freedom, a positive integer, maybe non-integer. |
mean, sd |
means and standard deviation of the normal distributed innovations. |
min, max |
lower and upper limits of the uniform distributed innovations. |
seed |
an integer value, the random number seed. |
n |
an integer, the number of random innovations to be generated. |
A simple portable random number generator for use in R and SPlus. We recommend to use this generator only for comparisons of calculations in R and Splus.
The generator is a linear congruential generator with parameters
LCG(a=13445, c=0, m=2^31-1, X=0). It is a simple random
number generator which passes the bitwise randomness test.
A vector of generated random innovations. The value of the
current seed is stored in the variable lcg.seed.
Altman, N.S. (1988); Bitwise Behavior of Random Number Generators, SIAM J. Sci. Stat. Comput., 9(5), September, 941–949.
## set.lcgseed - set.lcgseed(seed = 65890) ## runif.lcg - rnorm.lcg - rt.lcg - cbind(runif.lcg(10), rnorm.lcg(10), rt.lcg(10, df = 4)) ## get.lcgseed - get.lcgseed() ## Note, to overwrite rnorm, use # rnorm = rnorm.lcg # Going back to rnorm # rm(rnorm)