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DRANDGAUSSIAN / DRANDGAUSSIAN

Generates a vector of random variates from a Gaussian distribution with probability density function, f(X), where: f(X) = [exp([-(X - m)^2] / [2s^2])] / [s * sqrt(2 * Pi)]. Here m is the mean, (XMU), and s^2 is the variance, (VAR) of the distribution.

(Note that SRANDGAUSSIAN is the single precision version of DRANDGAUSSIAN. The argument lists of both routines are identical except that any double precision arguments of DRANDGAUSSIAN are replaced in SRANDGAUSSIAN by single precision arguments - type REAL in FORTRAN or type float in C).

— SUBROUTINE: DRANDGAUSSIAN (N,XMU,VAR,STATE,X,INFO)
— Input: INTEGER N

On input: number of variates required.
Constraint: N>=0.

— Input: DOUBLE PRECISION XMU

On input: mean of the distribution.

— Input: DOUBLE PRECISION VAR

On input: variance of the distribution.
Constraint: VAR>=0.

— Input/Output: INTEGER STATE(*)

The STATE vector holds information on the state of the base generator being used and as such its minimum length varies. Prior to calling DRANDGAUSSIAN STATE must have been initialized. See Initialization of the Base Generators for information on initialization of the STATE variable.
On input: the current state of the base generator.
On output: the updated state of the base generator.

— Output: DOUBLE PRECISION X(N)

On output: vector of variates from the specified distribution.

— Output: INTEGER INFO

On output: INFO is an error indicator. On successful exit, INFO contains 0. If INFO = -i on exit, the i-th argument had an illegal value. 

     Example:
     

     
          C      Generate 100 values from the Gaussian distribution
                 INTEGER LSTATE,N
                 PARAMETER (LSTATE=16,N=100)
                 INTEGER I,INFO,SEED(1),STATE(LSTATE)
                 DOUBLE PRECISION XMU,VAR
                 DOUBLE PRECISION X(N)
          C      Set the seed
                 SEED(1) = 1234
          
          C      Read in the distributional parameters
                 READ(5,*) XMU,VAR
          
          C      Initialize the STATE vector
                 CALL DRANDINITIALIZE(1,1,SEED,1,STATE,LSTATE,INFO)
          C      Generate N variates from the Gaussian distribution
                 CALL DRANDGAUSSIAN(N,XMU,VAR,STATE,X,INFO)
          
          C      Print the results
                 WRITE(6,*) (X(I),I=1,N)