Program g02bzfe
! G02BZF Example Program Text
! Mark 28.6 Release. NAG Copyright 2022.
! .. Use Statements ..
Use nag_library, Only: dscal, g02buf, g02bzf, nag_wp, x04ccf
! .. Implicit None Statement ..
Implicit None
! .. Parameters ..
Integer, Parameter :: nin = 5, nout = 6
! .. Local Scalars ..
Real (Kind=nag_wp) :: alpha, xsw, ysw
Integer :: b, i, ierr, ifail, lc, ldx, m, n
Character (1) :: mean, weight
! .. Local Arrays ..
Real (Kind=nag_wp), Allocatable :: wt(:), x(:,:), xc(:), xmean(:), &
yc(:), ymean(:)
! .. Executable Statements ..
Write (nout,*) 'G02BZF Example Program Results'
Write (nout,*)
Flush (nout)
! Skip heading in data file
Read (nin,*)
! Read in the problem defining variables
Read (nin,*) mean, m
! Allocate memory for output arrays
lc = (m*m+m)/2
Allocate (xmean(m),ymean(m),xc(lc),yc(lc))
! Loop over each block of data
b = 0
d_lp: Do
! Read in the number of observations in this block and the weight flag
Read (nin,*,Iostat=ierr) n, weight
If (ierr/=0) Then
Exit d_lp
End If
! Keep a running total of the number of blocks of data
b = b + 1
! Allocate arrays to hold data and read the current block of data in
ldx = n
Allocate (x(ldx,m))
If (weight=='W' .Or. weight=='w') Then
! Weighted
Allocate (wt(n))
Do i = 1, n
Read (nin,*) x(i,1:m), wt(i)
End Do
Else
! Unweighted
Allocate (wt(0))
Do i = 1, n
Read (nin,*) x(i,1:m)
End Do
End If
! Summarise this block of data
If (b==1) Then
! This is the first block of data, so summarise the data into XMEAN
! and XC
ifail = 0
Call g02buf(mean,weight,n,m,x,ldx,wt,xsw,xmean,xc,ifail)
Else
! This is not the first block of data, so summarise the data into
! YMEAN and YC
ifail = 0
Call g02buf(mean,weight,n,m,x,ldx,wt,ysw,ymean,yc,ifail)
! Update the running summaries
ifail = 0
Call g02bzf(mean,m,xsw,xmean,xc,ysw,ymean,yc,ifail)
End If
Deallocate (x,wt)
End Do d_lp
! Display results
Write (nout,*) 'Means'
Write (nout,99999) xmean(1:m)
Write (nout,*)
Flush (nout)
ifail = 0
Call x04ccf('Upper','Non-unit',m,xc,'Sums of squares and cross-products' &
,ifail)
If (xsw>1.0_nag_wp .And. (mean=='M' .Or. mean=='m')) Then
! Use DSCAL (F06EDF) to scale the sums of squares and cross-products
! matrix XC, and so convert it to a covariance matrix
alpha = 1.0_nag_wp/(xsw-1.0_nag_wp)
Call dscal(lc,alpha,xc,1)
Write (nout,*)
Flush (nout)
ifail = 0
Call x04ccf('Upper','Non-unit',m,xc,'Covariance matrix',ifail)
End If
99999 Format (1X,6F14.4)
End Program g02bzfe