@@ -210,19 +210,17 @@ section of the standard library reference.
210210
211211Sparse matrix solvers call functions from [ SuiteSparse] ( http://suitesparse.com ) . The following factorizations are available:
212212
213+ 1 .  [ ` cholesky ` ] (@ref   SparseArrays.CHOLMOD.cholesky)
214+ 2 .  [ ` ldlt ` ] (@ref   SparseArrays.CHOLMOD.ldlt)
215+ 3 .  [ ` lu ` ] (@ref   SparseArrays.UMFPACK.lu)
216+ 4 .  [ ` qr ` ] (@ref   SparseArrays.SPQR.qr)
217+ 
213218|  Type                  |  Description                                   | 
214219| :----------------------| :--------------------------------------------- | 
215220|  ` CHOLMOD.Factor `       |  Cholesky and LDLt factorizations              | 
216221|  ` UMFPACK.UmfpackLU `    |  LU factorization                              | 
217222|  ` SPQR.QRSparse `        |  QR factorization                              | 
218223
219- These factorizations are described in more detail in the [ Sparse Linear Algebra API section] (@ref   stdlib-sparse-linalg-api):
220- 
221- 1 .  [ ` cholesky ` ] (@ref   SparseArrays.CHOLMOD.cholesky)
222- 2 .  [ ` ldlt ` ] (@ref   SparseArrays.CHOLMOD.ldlt)
223- 3 .  [ ` lu ` ] (@ref   SparseArrays.UMFPACK.lu)
224- 4 .  [ ` qr ` ] (@ref   SparseArrays.SPQR.qr)
225- 
226224``` @meta 
227225DocTestSetup = nothing 
228226``` 
@@ -267,25 +265,6 @@ SparseArrays.ftranspose!
267265DocTestSetup = nothing 
268266``` 
269267
270- # [ Sparse Linear Algebra API] (@id   stdlib-sparse-linalg-api) 
271- 
272- ``` @docs 
273- SparseArrays.CHOLMOD.cholesky 
274- SparseArrays.CHOLMOD.cholesky! 
275- SparseArrays.CHOLMOD.lowrankupdate 
276- SparseArrays.CHOLMOD.lowrankupdate! 
277- SparseArrays.CHOLMOD.lowrankdowndate 
278- SparseArrays.CHOLMOD.lowrankdowndate! 
279- SparseArrays.CHOLMOD.lowrankupdowndate! 
280- SparseArrays.CHOLMOD.ldlt 
281- SparseArrays.UMFPACK.lu 
282- SparseArrays.SPQR.qr 
283- ``` 
284- 
285- ``` @meta 
286- DocTestSetup = nothing 
287- ``` 
288- 
289268# Noteworthy External Sparse Packages  
290269
291270Several other Julia packages provide sparse matrix implementations that should be mentioned:
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