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Revision 948ad5967298b4dc174f4d96511af60f38e9279e authored by Roger Koenker on 27 July 2019, 09:38:23 UTC, committed by cran-robot on 27 July 2019, 09:38:23 UTC
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linpack.f
C  The following routines are from LINPACK and do not seem to be part of
C  the standard R distro.
      subroutine dgedi(a,lda,n,ipvt,det,work,job)
      integer lda,n,ipvt(*),job
      double precision a(lda,*),det(2),work(*)
c
c     dgedi computes the determinant and inverse of a matrix
c     using the factors computed by dgeco or dgefa.
c
c     on entry
c
c        a       double precision(lda, n)
c                the output from dgeco or dgefa.
c
c        lda     integer
c                the leading dimension of the array  a .
c
c        n       integer
c                the order of the matrix  a .
c
c        ipvt    integer(n)
c                the pivot vector from dgeco or dgefa.
c
c        work    double precision(n)
c                work vector.  contents destroyed.
c
c        job     integer
c                = 11   both determinant and inverse.
c                = 01   inverse only.
c                = 10   determinant only.
c
c     on return
c
c        a       inverse of original matrix if requested.
c                otherwise unchanged.
c
c        det     double precision(2)
c                determinant of original matrix if requested.
c                otherwise not referenced.
c                determinant = det(1) * 10.0**det(2)
c                with  1.0 .le. dabs(det(1)) .lt. 10.0
c                or  det(1) .eq. 0.0 .
c
c     error condition
c
c        a division by zero will occur if the input factor contains
c        a zero on the diagonal and the inverse is requested.
c        it will not occur if the subroutines are called correctly
c        and if dgeco has set rcond .gt. 0.0 or dgefa has set
c        info .eq. 0 .
c
c     linpack. this version dated 08/14/78 .
c     cleve moler, university of new mexico, argonne national lab.
c
c     subroutines and functions
c
c     blas daxpy,dscal,dswap
c     fortran dabs,mod
c
c     internal variables
c
      double precision t
      double precision ten
      integer i,j,k,kb,kp1,l,nm1
c
c
c     compute determinant
c
      if (job/10 .eq. 0) go to 70
         det(1) = 1.0d0
         det(2) = 0.0d0
         ten = 10.0d0
         do 50 i = 1, n
            if (ipvt(i) .ne. i) det(1) = -det(1)
            det(1) = a(i,i)*det(1)
c        ...exit
            if (det(1) .eq. 0.0d0) go to 60
   10       if (dabs(det(1)) .ge. 1.0d0) go to 20
               det(1) = ten*det(1)
               det(2) = det(2) - 1.0d0
            go to 10
   20       continue
   30       if (dabs(det(1)) .lt. ten) go to 40
               det(1) = det(1)/ten
               det(2) = det(2) + 1.0d0
            go to 30
   40       continue
   50    continue
   60    continue
   70 continue
c
c     compute inverse(u)
c
      if (mod(job,10) .eq. 0) go to 150
         do 100 k = 1, n
            a(k,k) = 1.0d0/a(k,k)
            t = -a(k,k)
            call dscal(k-1,t,a(1,k),1)
            kp1 = k + 1
            if (n .lt. kp1) go to 90
            do 80 j = kp1, n
               t = a(k,j)
               a(k,j) = 0.0d0
               call daxpy(k,t,a(1,k),1,a(1,j),1)
   80       continue
   90       continue
  100    continue
c
c        form inverse(u)*inverse(l)
c
         nm1 = n - 1
         if (nm1 .lt. 1) go to 140
         do 130 kb = 1, nm1
            k = n - kb
            kp1 = k + 1
            do 110 i = kp1, n
               work(i) = a(i,k)
               a(i,k) = 0.0d0
  110       continue
            do 120 j = kp1, n
               t = work(j)
               call daxpy(n,t,a(1,j),1,a(1,k),1)
  120       continue
            l = ipvt(k)
            if (l .ne. k) call dswap(n,a(1,k),1,a(1,l),1)
  130    continue
  140    continue
  150 continue
      return
      end
      subroutine dgeco(a,lda,n,ipvt,rcond,z)
      integer lda,n,ipvt(*)
      double precision a(lda,*),z(*)
      double precision rcond
c
c     dgeco factors a double precision matrix by gaussian elimination
c     and estimates the condition of the matrix.
c
c
c     if  rcond  is not needed, dgefa is slightly faster.
c     to solve  a*x = b , follow dgeco by dgesl.
c     to compute  inverse(a)*c , follow dgeco by dgesl.
c     to compute  determinant(a) , follow dgeco by dgedi.
c     to compute  inverse(a) , follow dgeco by dgedi.
c
c     on entry
c
c        a       double precision(lda, n)
c                the matrix to be factored.
c
c        lda     integer
c                the leading dimension of the array  a .
c
c        n       integer
c                the order of the matrix  a .
c
c     on return
c
c        a       an upper triangular matrix and the multipliers
c                which were used to obtain it.
c                the factorization can be written  a = l*u  where
c                l  is a product of permutation and unit lower
c                triangular matrices and  u  is upper triangular.
c
c        ipvt    integer(n)
c                an integer vector of pivot indices.
c
c        rcond   double precision
c                an estimate of the reciprocal condition of  a .
c                for the system  a*x = b , relative perturbations
c                in  a  and  b  of size  epsilon  may cause
c                relative perturbations in  x  of size  epsilon/rcond .
c                if  rcond  is so small that the logical expression
c                           1.0 + rcond .eq. 1.0
c                is true, then  a  may be singular to working
c                precision.  in particular,  rcond  is zero  if
c                exact singularity is detected or the estimate
c                underflows.
c
c        z       double precision(n)
c                a work vector whose contents are usually unimportant.
c                if  a  is close to a singular matrix, then  z  is
c                an approximate null vector in the sense that
c                norm(a*z) = rcond*norm(a)*norm(z) .
c
c     linpack. this version dated 08/14/78 .
c     cleve moler, university of new mexico, argonne national lab.
c
c     subroutines and functions
c
c     linpack dgefa
c     blas daxpy,ddot,dscal,dasum
c     fortran dabs,dmax1,dsign
c
c     internal variables
c
      double precision ddot,ek,t,wk,wkm
      double precision anorm,s,dasum,sm,ynorm
      integer info,j,k,kb,kp1,l
c
c
c     compute 1-norm of a
c
      anorm = 0.0d0
      do 10 j = 1, n
         anorm = dmax1(anorm,dasum(n,a(1,j),1))
   10 continue
c
c     factor
c
      call dgefa(a,lda,n,ipvt,info)
c
c     rcond = 1/(norm(a)*(estimate of norm(inverse(a)))) .
c     estimate = norm(z)/norm(y) where  a*z = y  and  trans(a)*y = e .
c     trans(a)  is the transpose of a .  the components of  e  are
c     chosen to cause maximum local growth in the elements of w  where
c     trans(u)*w = e .  the vectors are frequently rescaled to avoid
c     overflow.
c
c     solve trans(u)*w = e
c
      ek = 1.0d0
      do 20 j = 1, n
         z(j) = 0.0d0
   20 continue
      do 100 k = 1, n
         if (z(k) .ne. 0.0d0) ek = dsign(ek,-z(k))
         if (dabs(ek-z(k)) .le. dabs(a(k,k))) go to 30
            s = dabs(a(k,k))/dabs(ek-z(k))
            call dscal(n,s,z,1)
            ek = s*ek
   30    continue
         wk = ek - z(k)
         wkm = -ek - z(k)
         s = dabs(wk)
         sm = dabs(wkm)
         if (a(k,k) .eq. 0.0d0) go to 40
            wk = wk/a(k,k)
            wkm = wkm/a(k,k)
         go to 50
   40    continue
            wk = 1.0d0
            wkm = 1.0d0
   50    continue
         kp1 = k + 1
         if (kp1 .gt. n) go to 90
            do 60 j = kp1, n
               sm = sm + dabs(z(j)+wkm*a(k,j))
               z(j) = z(j) + wk*a(k,j)
               s = s + dabs(z(j))
   60       continue
            if (s .ge. sm) go to 80
               t = wkm - wk
               wk = wkm
               do 70 j = kp1, n
                  z(j) = z(j) + t*a(k,j)
   70          continue
   80       continue
   90    continue
         z(k) = wk
  100 continue
      s = 1.0d0/dasum(n,z,1)
      call dscal(n,s,z,1)
c
c     solve trans(l)*y = w
c
      do 120 kb = 1, n
         k = n + 1 - kb
         if (k .lt. n) z(k) = z(k) + ddot(n-k,a(k+1,k),1,z(k+1),1)
         if (dabs(z(k)) .le. 1.0d0) go to 110
            s = 1.0d0/dabs(z(k))
            call dscal(n,s,z,1)
  110    continue
         l = ipvt(k)
         t = z(l)
         z(l) = z(k)
         z(k) = t
  120 continue
      s = 1.0d0/dasum(n,z,1)
      call dscal(n,s,z,1)
c
      ynorm = 1.0d0
c
c     solve l*v = y
c
      do 140 k = 1, n
         l = ipvt(k)
         t = z(l)
         z(l) = z(k)
         z(k) = t
         if (k .lt. n) call daxpy(n-k,t,a(k+1,k),1,z(k+1),1)
         if (dabs(z(k)) .le. 1.0d0) go to 130
            s = 1.0d0/dabs(z(k))
            call dscal(n,s,z,1)
            ynorm = s*ynorm
  130    continue
  140 continue
      s = 1.0d0/dasum(n,z,1)
      call dscal(n,s,z,1)
      ynorm = s*ynorm
c
c     solve  u*z = v
c
      do 160 kb = 1, n
         k = n + 1 - kb
         if (dabs(z(k)) .le. dabs(a(k,k))) go to 150
            s = dabs(a(k,k))/dabs(z(k))
            call dscal(n,s,z,1)
            ynorm = s*ynorm
  150    continue
         if (a(k,k) .ne. 0.0d0) z(k) = z(k)/a(k,k)
         if (a(k,k) .eq. 0.0d0) z(k) = 1.0d0
         t = -z(k)
         call daxpy(k-1,t,a(1,k),1,z(1),1)
  160 continue
c     make znorm = 1.0
      s = 1.0d0/dasum(n,z,1)
      call dscal(n,s,z,1)
      ynorm = s*ynorm
c
      if (anorm .ne. 0.0d0) rcond = ynorm/anorm
      if (anorm .eq. 0.0d0) rcond = 0.0d0
      return
      end

      subroutine dgefa(a,lda,n,ipvt,info)
c      use numerical_libraries
	
      integer lda,n,ipvt(*),info
      double precision a(lda,*)
c
c     dgefa factors a double precision matrix by gaussian elimination.
c
c     dgefa is usually called by dgeco, but it can be called
c     directly with a saving in time if  rcond  is not needed.
c     (time for dgeco) = (1 + 9/n)*(time for dgefa) .
c
c     on entry
c
c        a       double precision(lda, n)
c                the matrix to be factored.
c
c        lda     integer
c                the leading dimension of the array  a .
c
c        n       integer
c                the order of the matrix  a .
c
c     on return
c
c        a       an upper triangular matrix and the multipliers
c                which were used to obtain it.
c                the factorization can be written  a = l*u  where
c                l  is a product of permutation and unit lower
c                triangular matrices and  u  is upper triangular.
c
c        ipvt    integer(n)
c                an integer vector of pivot indices.
c
c        info    integer
c                = 0  normal value.
c                = k  if  u(k,k) .eq. 0.0 .  this is not an error
c                     condition for this subroutine, but it does
c                     indicate that dgesl or dgedi will divide by zero
c                     if called.  use  rcond  in dgeco for a reliable
c                     indication of singularity.
c
c     linpack. this version dated 08/14/78 .
c     cleve moler, university of new mexico, argonne national lab.
c
c     subroutines and functions
c
c     blas daxpy,dscal,idamax
c
c     internal variables
c
      double precision t
c           integer idamax,j,k,kp1,l,nm1
	 integer j,k,kp1,l,nm1
c
c
c     gaussian elimination with partial pivoting
c
      info = 0
      nm1 = n - 1
      if (nm1 .lt. 1) go to 70
      do 60 k = 1, nm1
         kp1 = k + 1
c
c        find l = pivot index
c
         l = idamax(n-k+1,a(k,k),1) + k - 1
         ipvt(k) = l
c
c        zero pivot implies this column already triangularized
c
         if (a(l,k) .eq. 0.0d0) go to 40
c
c           interchange if necessary
c
            if (l .eq. k) go to 10
               t = a(l,k)
               a(l,k) = a(k,k)
               a(k,k) = t
   10       continue
c
c           compute multipliers
c
            t = -1.0d0/a(k,k)
            call dscal(n-k,t,a(k+1,k),1)
c
c           row elimination with column indexing
c
            do 30 j = kp1, n
               t = a(l,j)
               if (l .eq. k) go to 20
                  a(l,j) = a(k,j)
                  a(k,j) = t
   20          continue
               call daxpy(n-k,t,a(k+1,k),1,a(k+1,j),1)
   30       continue
         go to 50
   40    continue
            info = k
   50    continue
   60 continue
   70 continue
      ipvt(n) = n
      if (a(n,n) .eq. 0.0d0) info = n
      return
      end
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