```    Program g08rbfe

!     G08RBF Example Program Text

!     Mark 26.1 Release. NAG Copyright 2017.

!     .. Use Statements ..
Use nag_library, Only: g08rbf, nag_wp
!     .. Implicit None Statement ..
Implicit None
!     .. Parameters ..
Integer, Parameter               :: nin = 5, nout = 6
!     .. Local Scalars ..
Real (Kind=nag_wp)               :: gamma, tol
Integer                          :: i, ifail, ip, j, ldprvr, ldx, liwa,  &
lparest, lvapvec, lwork, nmax, ns,   &
nsum
!     .. Local Arrays ..
Real (Kind=nag_wp), Allocatable  :: eta(:), parest(:), prvr(:,:),        &
vapvec(:), work(:), x(:,:), y(:),    &
zin(:)
Integer, Allocatable             :: icen(:), irank(:), iwa(:), nv(:)
!     .. Intrinsic Procedures ..
Intrinsic                        :: maxval, sum
!     .. Executable Statements ..
Write (nout,*) 'G08RBF Example Program Results'
Write (nout,*)

!     Skip heading in data file

!     Read number of samples, number of parameters to be fitted,
!     distribution power parameter and tolerance criterion for ties.
Read (nin,*) ns, ip, gamma, tol

Allocate (nv(ns))

!     Read the number of observations in each sample

!     Calculate NSUM, NMAX and various array lengths
nsum = sum(nv(1:ns))
nmax = maxval(nv(1:ns))
ldx = nsum
ldprvr = ip + 1
lvapvec = nmax*(nmax+1)/2
lparest = 4*ip + 1
lwork = nmax*(ip+1)
liwa = 4*nmax

Allocate (y(nsum),x(ldx,ip),icen(nsum),prvr(ldprvr,ip),irank(nmax),      &
zin(nmax),eta(nmax),vapvec(lvapvec),parest(lparest),work(lwork),       &
iwa(liwa))

!     Read in observations, design matrix and censoring variable

!     Display input information
Write (nout,99999) 'Number of samples =', ns
Write (nout,99999) 'Number of parameters fitted =', ip
Write (nout,99998) 'Distribution power parameter =', gamma
Write (nout,99998) 'Tolerance for ties =', tol

ifail = 0
Call g08rbf(ns,nv,nsum,y,ip,x,ldx,icen,gamma,nmax,tol,prvr,ldprvr,irank, &
zin,eta,vapvec,parest,work,lwork,iwa,ifail)

!     Display results
Write (nout,*)
Write (nout,*) 'Score statistic'
Write (nout,99997) parest(1:ip)
Write (nout,*)
Write (nout,*) 'Covariance matrix of score statistic'
Do j = 1, ip
Write (nout,99997) prvr(1:j,j)
End Do
Write (nout,*)
Write (nout,*) 'Parameter estimates'
Write (nout,99997) parest((ip+1):(2*ip))
Write (nout,*)
Write (nout,*) 'Covariance matrix of parameter estimates'
Do i = 1, ip
Write (nout,99997) prvr(i+1,1:i)
End Do
Write (nout,*)
Write (nout,99996) 'Chi-squared statistic =', parest(2*ip+1), ' with',   &
ip, ' d.f.'
Write (nout,*)
Write (nout,*) 'Standard errors of estimates and'
Write (nout,*) 'approximate z-statistics'
Write (nout,99995)(parest(2*ip+1+i),parest(3*ip+1+i),i=1,ip)

99999 Format (1X,A,I2)
99998 Format (1X,A,F10.5)
99997 Format (1X,F9.3)
99996 Format (1X,A,F9.3,A,I2,A)
99995 Format (1X,F9.3,F14.3)
End Program g08rbfe
```