Ranlib
======

The ranlib libary from University of Texas contains  a large number of random number generators.

Beta distribution.
     @betarand(A,B) generates  a single random deviate from the beta distribution with parameters A and B.  The density of the beta distribution is

                         x^(a-1) * (1-x)^(b-1) / B(a,b) for 0 < x < 1

Chi Squared Distribution
     @chirand(DF) generates a random deviate from a chisquare distribution with DF degrees of freedom. DF must be positive.

Exponential Distribution
     @exprand(AV) generates a single random deviate from an exponential distribution with mean AV.

F distribution
     @fdist(DFN,DFD) generates a random deviate from the F distribution with DFN degrees of freedom in the numerator and DFD degrees of freedom in the denominator.  Both arguments must be positive.

Gamma distribution
     @gammarand(A,R) generates random deviates from the gamma distribution whose density is

                    (a**r)/gamma(r) * x**(r-1) * exp(-a*x)

     where A is the  location parameter of Gamma distribution and R is the  shape parameter of Gamma distribution.

Non Central Chi Square Distribution
     @nchirand(DF,XNONC) generates random deviate  from the  distribution  of a  noncentral chisquare with DF degrees  of freedom and noncentrality  parameter XNONC. DF must be greater than 1, and XNONC must be positive.

Non Central F distribution
     @nfrand(DFN,DFD,XNONC) generates a random deviate from the  noncentral F distribution with DFN degrees of freedom in the numerator, DFD      degrees of freedom in the denominator, and noncentrality parameter XNONC. DFN must be at least 1, DFD must be positive, and XNONC must be non-negative.

Normal Distribution
     @normalrand(MU,SD) generates a single random deviate from a normal distribution with mean MU, and standard deviation, SD.

Uniform Distribution
     @unirand(LOW,HIGH) generates a real uniformly distributed between LOW and HIGH.

Binomial Distribution
     @binomialrand(N,P)         generates a single random deviate from a binomial       distribution with N trials, and the  probability of an event in each trial is P. The result is a random deviate yielding the number of events from N independent trials, each of which has  a probability of event P.

Poisson Distribution
     @poisonrand(MU) generates a single random deviate from a Poisson distribution with mean MU.

Uniform Integers
     @intunirand(LOW,HIGH) generates an integer uniformly distributed between LOW and HIGH.