```    Program g02dafe

!     G02DAF Example Program Text

!     Mark 26 Release. NAG Copyright 2016.

!     .. Use Statements ..
Use nag_library, Only: g02buf, g02daf, nag_wp
!     .. Implicit None Statement ..
Implicit None
!     .. Parameters ..
Integer, Parameter               :: nin = 5, nout = 6
!     .. Local Scalars ..
Real (Kind=nag_wp)               :: aic, arsq, en, mult, rsq, rss, sw,   &
tol
Integer                          :: i, idf, ifail, ip, irank, ldq, ldx,  &
lwt, m, n
Logical                          :: svd
Character (1)                    :: mean, weight
!     .. Local Arrays ..
Real (Kind=nag_wp), Allocatable  :: b(:), cov(:), h(:), p(:), q(:,:),    &
res(:), se(:), wk(:), wt(:), x(:,:), &
y(:)
Real (Kind=nag_wp)               :: c(1), wmean(1)
Integer, Allocatable             :: isx(:)
!     .. Intrinsic Procedures ..
Intrinsic                        :: count, log, real
!     .. Executable Statements ..
Write (nout,*) 'G02DAF Example Program Results'
Write (nout,*)

!     Skip heading in data file

!     Read in the problem size
Read (nin,*) n, m, weight, mean

If (weight=='W' .Or. weight=='w') Then
lwt = n
Else
lwt = 0
End If
ldx = n
Allocate (x(ldx,m),y(n),wt(lwt),isx(m))

If (lwt>0) Then
Else
End If

!     Read in variable inclusion flags

!     Calculate IP
ip = count(isx(1:m)>0)
If (mean=='M' .Or. mean=='m') Then
ip = ip + 1
End If

ldq = n
Allocate (b(ip),cov((ip*ip+ip)/2),h(n),p(ip*(ip+                         &
2)),q(ldq,ip+1),res(n),se(ip),wk(ip*ip+5*(ip-1)))

!     Use suggested value for tolerance
tol = 0.000001E0_nag_wp

!     Fit general linear regression model
ifail = -1
ldq,svd,irank,p,tol,wk,ifail)
If (ifail/=0) Then
If (ifail/=5) Then
Go To 100
End If
End If

!     Calculate (weighted) total sums of squares, adjusted for mean if
!     required
!     If in G02DAF, an intercept is added to the regression by including a
!     column of 1's in X, rather than by using the MEAN argument then
!     MEAN = 'M' should be used in this call to G02BUF.
ifail = 0
Call g02buf(mean,weight,n,1,y,n,wt,sw,wmean,c,ifail)

!     Get effective number of observations (=N if there are no zero weights)
en = real(idf+irank,kind=nag_wp)

!     Calculate R-squared, corrected R-squared and AIC
If (mean=='M' .Or. mean=='m') Then
mult = (en-1.0E0_nag_wp)/(en-real(irank,kind=nag_wp))
Else
mult = en/(en-real(irank,kind=nag_wp))
End If
arsq = 1.0_nag_wp - mult*(1.0_nag_wp-rsq)

!     Display results
If (svd) Then
Write (nout,99999) 'Model not of full rank, rank = ', irank
Write (nout,*)
End If
Write (nout,99998) 'Residual sum of squares = ', rss
Write (nout,99999) 'Degrees of freedom      = ', idf
Write (nout,99998) 'R-squared               = ', rsq
Write (nout,99998) 'Adjusted R-squared      = ', arsq
Write (nout,99998) 'AIC                     = ', aic
Write (nout,*)
Write (nout,*) 'Variable   Parameter estimate   Standard error'
Write (nout,*)
If (ifail==0) Then
Write (nout,99997)(i,b(i),se(i),i=1,ip)
Else
Write (nout,99996)(i,b(i),i=1,ip)
End If
Write (nout,*)
Write (nout,*) '   Obs          Residuals              H'
Write (nout,*)
Write (nout,99997)(i,res(i),h(i),i=1,n)

100   Continue

99999 Format (1X,A,I4)
99998 Format (1X,A,E12.4)
99997 Format (1X,I6,2E20.4)
99996 Format (1X,I6,E20.4)
End Program g02dafe
```