Initializes a reference vector for use with DRANDMULTISTUDENTSTR. Reference vector is for a Multivariate Students T distribution with probability density function, \(f (X)\), where:
\[f(X) = \frac{\Gamma\left(\frac{\nu + M}{2}\right)} {(\nu \pi)^{\frac{M}{2}} \Gamma\left(\frac{\nu}{2}\right)|C|^{\frac{1}{2}}} \left(1 + \frac{1}{\nu} (X - \mu)^T C^{-1} (X - \mu)\right)^{-\frac{\nu + M}{2}}\]
where μ is the vector of means, XMU and ν is the degrees of freedom, DF.
C Generate 100 values from the
C Multivariate Students T distribution
INTEGER LSTATE,N, MM
PARAMETER (LSTATE=16,N=100,MM=10)
INTEGER I,J,INFO,SEED(1),STATE(LSTATE)
INTEGER LDC,LDX,M,DF
DOUBLE PRECISION X(N,MM),XMU(MM),C(MM,MM)
INTEGER LREF
DOUBLE PRECISION REF(1000)
C Set array sizes
LDC = MM
LDX = N
C Set the seed
SEED(1) = 1234
C Read in the distributional parameters
READ(5,*) M,DF
READ(5,*) (XMU(I),I=1,M)
DO 20 I = 1,M
READ(5,*) (C(I,J),J=1,M)
20 CONTINUE
C Initialize the STATE vector
CALL DRANDINITIALIZE(1,1,SEED,1,STATE,LSTATE,INFO)
C Initialize the reference vector
LREF = 1000
CALL DRANDMULTINORMALREFERENCE(M,XMU,C,LDC,REF,LREF,INFO)
C Generate N variates from the
C Multivariate Normal distribution
CALL DRANDMULTISTUDENTSTR(N,REF,STATE,X,LDX,INFO)
C Print the results
DO 40 I = 1,N
WRITE(6,*) (X(I,J),J=1,M)
40 CONTINUE