defficient spells deficient

diff --git a/SRC/cgejsv.f b/SRC/cgejsv.f
index f69ab9d..0641e42 100644 (file)
--- a/SRC/cgejsv.f
+++ b/SRC/cgejsv.f
@@ -85,7 +85,7 @@
 *>              rows, then using this condition number gives too pessimistic
 *>              error bound.
 *>       = 'A': Small singular values are the noise and the matrix is treated
-*>              as numerically rank defficient. The error in the computed
+*>              as numerically rank deficient. The error in the computed
 *>              singular values is bounded by f(m,n)*epsilon*||A||.
 *>              The computed SVD A = U * S * V^* restores A up to
 *>              f(m,n)*epsilon*||A||.
@@ -469,7 +469,7 @@
 *>     The rank revealing QR factorization (in this code: CGEQP3) should be
 *>  implemented as in [3]. We have a new version of CGEQP3 under development
 *>  that is more robust than the current one in LAPACK, with a cleaner cut in
-*>  rank defficient cases. It will be available in the SIGMA library [4].
+*>  rank deficient cases. It will be available in the SIGMA library [4].
 *>  If M is much larger than N, it is obvious that the initial QRF with
 *>  column pivoting can be preprocessed by the QRF without pivoting. That
 *>  well known trick is not used in CGEJSV because in some cases heavy row
@@ -1021,7 +1021,7 @@
       ELSE IF ( L2RANK ) THEN
 *        .. similarly as above, only slightly more gentle (less agressive).
 *        Sudden drop on the diagonal of R1 is used as the criterion for
-*        close-to-rank-defficient.
+*        close-to-rank-deficient.
          TEMP1 = SQRT(SFMIN)
          DO 3401 p = 2, N
             IF ( ( ABS(A(p,p)) .LT. (EPSLN*ABS(A(p-1,p-1))) ) .OR.

diff --git a/SRC/dgejsv.f b/SRC/dgejsv.f
index 3488f26..64f0908 100644 (file)
--- a/SRC/dgejsv.f
+++ b/SRC/dgejsv.f
@@ -87,7 +87,7 @@
 *>             rows, then using this condition number gives too pessimistic
 *>             error bound.
 *>       = 'A': Small singular values are the noise and the matrix is treated
-*>             as numerically rank defficient. The error in the computed
+*>             as numerically rank deficient. The error in the computed
 *>             singular values is bounded by f(m,n)*epsilon*||A||.
 *>             The computed SVD A = U * S * V^t restores A up to
 *>             f(m,n)*epsilon*||A||.
@@ -428,7 +428,7 @@
 *>     The rank revealing QR factorization (in this code: DGEQP3) should be
 *>  implemented as in [3]. We have a new version of DGEQP3 under development
 *>  that is more robust than the current one in LAPACK, with a cleaner cut in
-*>  rank defficient cases. It will be available in the SIGMA library [4].
+*>  rank deficient cases. It will be available in the SIGMA library [4].
 *>  If M is much larger than N, it is obvious that the initial QRF with
 *>  column pivoting can be preprocessed by the QRF without pivoting. That
 *>  well known trick is not used in DGEJSV because in some cases heavy row
@@ -967,7 +967,7 @@
       ELSE IF ( L2RANK ) THEN
 *        .. similarly as above, only slightly more gentle (less agressive).
 *        Sudden drop on the diagonal of R1 is used as the criterion for
-*        close-to-rank-defficient.
+*        close-to-rank-deficient.
          TEMP1 = DSQRT(SFMIN)
          DO 3401 p = 2, N
             IF ( ( DABS(A(p,p)) .LT. (EPSLN*DABS(A(p-1,p-1))) ) .OR.

diff --git a/SRC/sgejsv.f b/SRC/sgejsv.f
index 4054a59..a52e39b 100644 (file)
--- a/SRC/sgejsv.f
+++ b/SRC/sgejsv.f
@@ -87,7 +87,7 @@
 *>              rows, then using this condition number gives too pessimistic
 *>              error bound.
 *>       = 'A': Small singular values are the noise and the matrix is treated
-*>              as numerically rank defficient. The error in the computed
+*>              as numerically rank deficient. The error in the computed
 *>              singular values is bounded by f(m,n)*epsilon*||A||.
 *>              The computed SVD A = U * S * V^t restores A up to
 *>              f(m,n)*epsilon*||A||.
@@ -428,7 +428,7 @@
 *>     The rank revealing QR factorization (in this code: SGEQP3) should be
 *>  implemented as in [3]. We have a new version of SGEQP3 under development
 *>  that is more robust than the current one in LAPACK, with a cleaner cut in
-*>  rank defficient cases. It will be available in the SIGMA library [4].
+*>  rank deficient cases. It will be available in the SIGMA library [4].
 *>  If M is much larger than N, it is obvious that the initial QRF with
 *>  column pivoting can be preprocessed by the QRF without pivoting. That
 *>  well known trick is not used in SGEJSV because in some cases heavy row
@@ -967,7 +967,7 @@
       ELSE IF ( L2RANK ) THEN
 *        .. similarly as above, only slightly more gentle (less agressive).
 *        Sudden drop on the diagonal of R1 is used as the criterion for
-*        close-to-rank-defficient.
+*        close-to-rank-deficient.
          TEMP1 = SQRT(SFMIN)
          DO 3401 p = 2, N
             IF ( ( ABS(A(p,p)) .LT. (EPSLN*ABS(A(p-1,p-1))) ) .OR.

diff --git a/SRC/zgejsv.f b/SRC/zgejsv.f
index 95da5e6..fa85af0 100644 (file)
--- a/SRC/zgejsv.f
+++ b/SRC/zgejsv.f
@@ -85,7 +85,7 @@
 *>              rows, then using this condition number gives too pessimistic
 *>              error bound.
 *>       = 'A': Small singular values are the noise and the matrix is treated
-*>              as numerically rank defficient. The error in the computed
+*>              as numerically rank deficient. The error in the computed
 *>              singular values is bounded by f(m,n)*epsilon*||A||.
 *>              The computed SVD A = U * S * V^* restores A up to
 *>              f(m,n)*epsilon*||A||.
@@ -470,7 +470,7 @@
 *>     The rank revealing QR factorization (in this code: ZGEQP3) should be
 *>  implemented as in [3]. We have a new version of ZGEQP3 under development
 *>  that is more robust than the current one in LAPACK, with a cleaner cut in
-*>  rank defficient cases. It will be available in the SIGMA library [4].
+*>  rank deficient cases. It will be available in the SIGMA library [4].
 *>  If M is much larger than N, it is obvious that the initial QRF with
 *>  column pivoting can be preprocessed by the QRF without pivoting. That
 *>  well known trick is not used in ZGEJSV because in some cases heavy row
@@ -1026,7 +1026,7 @@
       ELSE IF ( L2RANK ) THEN
 *        .. similarly as above, only slightly more gentle (less agressive).
 *        Sudden drop on the diagonal of R1 is used as the criterion for
-*        close-to-rank-defficient.
+*        close-to-rank-deficient.
          TEMP1 = DSQRT(SFMIN)
          DO 3401 p = 2, N
             IF ( ( ABS(A(p,p)) .LT. (EPSLN*ABS(A(p-1,p-1))) ) .OR.