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authorJulien Langou <julien.langou@ucdenver.edu>2016-11-24 09:41:52 +0100
committerJulien Langou <julien.langou@ucdenver.edu>2016-11-24 09:41:52 +0100
commit0d36145952f8e077b6bd056114b6be003152e693 (patch)
treebf1becb10389151340c025bf53f102c2513f94fa
parentfd8bd3594465d89a6ef83310c818ae9701196d00 (diff)
defficient spells deficient
-rw-r--r--SRC/cgejsv.f6
-rw-r--r--SRC/dgejsv.f6
-rw-r--r--SRC/sgejsv.f6
-rw-r--r--SRC/zgejsv.f6
4 files changed, 12 insertions, 12 deletions
diff --git a/SRC/cgejsv.f b/SRC/cgejsv.f
index f69ab9d1..0641e42c 100644
--- 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 3488f262..64f0908f 100644
--- 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 4054a593..a52e39b3 100644
--- 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 95da5e67..fa85af00 100644
--- 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.