The function may be called by the names: f07wdc, nag_lapacklin_dpftrf or nag_dpftrf.
3Description
f07wdc forms the Cholesky factorization of a real symmetric positive definite matrix $A$ either as $A={U}^{\mathrm{T}}U$ if ${\mathbf{uplo}}=\mathrm{Nag\_Upper}$ or $A=L{L}^{\mathrm{T}}$ if ${\mathbf{uplo}}=\mathrm{Nag\_Lower}$, where $U$ is an upper triangular matrix and $L$ is a lower triangular, stored in RFP format.
The RFP storage format is described in Section 3.4.3 in the F07 Chapter Introduction.
Gustavson F G, Waśniewski J, Dongarra J J and Langou J (2010) Rectangular full packed format for Cholesky's algorithm: factorization, solution, and inversion ACM Trans. Math. Software37, 2
5Arguments
1: $\mathbf{order}$ – Nag_OrderTypeInput
On entry: the order argument specifies the two-dimensional storage scheme being used, i.e., row-major ordering or column-major ordering. C language defined storage is specified by ${\mathbf{order}}=\mathrm{Nag\_RowMajor}$. See Section 3.1.3 in the Introduction to the NAG Library CL Interface for a more detailed explanation of the use of this argument.
Constraint:
${\mathbf{order}}=\mathrm{Nag\_RowMajor}$ or $\mathrm{Nag\_ColMajor}$.
2: $\mathbf{transr}$ – Nag_RFP_StoreInput
On entry: specifies whether the RFP representation of $A$ is normal or transposed.
${\mathbf{transr}}=\mathrm{Nag\_RFP\_Normal}$
The matrix $A$ is stored in normal RFP format.
${\mathbf{transr}}=\mathrm{Nag\_RFP\_Trans}$
The matrix $A$ is stored in transposed RFP format.
Constraint:
${\mathbf{transr}}=\mathrm{Nag\_RFP\_Normal}$ or $\mathrm{Nag\_RFP\_Trans}$.
3: $\mathbf{uplo}$ – Nag_UploTypeInput
On entry: specifies whether the upper or lower triangular part of $A$ is stored.
${\mathbf{uplo}}=\mathrm{Nag\_Upper}$
The upper triangular part of $A$ is stored, and $A$ is factorized as ${U}^{\mathrm{T}}U$, where $U$ is upper triangular.
${\mathbf{uplo}}=\mathrm{Nag\_Lower}$
The lower triangular part of $A$ is stored, and $A$ is factorized as $L{L}^{\mathrm{T}}$, where $L$ is lower triangular.
Constraint:
${\mathbf{uplo}}=\mathrm{Nag\_Upper}$ or $\mathrm{Nag\_Lower}$.
On entry: the upper or lower triangular part (as specified by uplo) of the $n\times n$ symmetric matrix $A$, in either normal or transposed RFP format (as specified by transr). The storage format is described in detail in Section 3.4.3 in the F07 Chapter Introduction.
On exit: if ${\mathbf{fail}}\mathbf{.}\mathbf{code}=$ NE_NOERROR, the factor $U$ or $L$ from the Cholesky factorization $A={U}^{\mathrm{T}}U$ or $A=L{L}^{\mathrm{T}}$, in the same storage format as $A$.
6: $\mathbf{fail}$ – NagError *Input/Output
The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).
6Error Indicators and Warnings
NE_ALLOC_FAIL
Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
NE_BAD_PARAM
On entry, argument $\u27e8\mathit{\text{value}}\u27e9$ had an illegal value.
NE_INT
On entry, ${\mathbf{n}}=\u27e8\mathit{\text{value}}\u27e9$.
Constraint: ${\mathbf{n}}\ge 0$.
NE_INTERNAL_ERROR
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
See Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
NE_MAT_NOT_POS_DEF
The leading minor of order $\u27e8\mathit{\text{value}}\u27e9$ is not positive definite and the factorization could not be completed. Hence $A$ itself is not positive definite. This may indicate an error in forming the matrix $A$.
There is no function specifically designed to factorize a symmetric matrix stored in RFP format which is not positive definite; the matrix must be treated as a full symmetric matrix, by calling f07mdc.
NE_NO_LICENCE
Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library CL Interface for further information.
7Accuracy
If ${\mathbf{uplo}}=\mathrm{Nag\_Upper}$, the computed factor $U$ is the exact factor of a perturbed matrix $A+E$, where
$c\left(n\right)$ is a modest linear function of $n$, and $\epsilon $ is the machine precision.
If ${\mathbf{uplo}}=\mathrm{Nag\_Lower}$, a similar statement holds for the computed factor $L$. It follows that $\left|{e}_{ij}\right|\le c\left(n\right)\epsilon \sqrt{{a}_{ii}{a}_{jj}}$.
8Parallelism and Performance
f07wdc is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
f07wdc makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.
Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this function. Please also consult the Users' Note for your implementation for any additional implementation-specific information.
9Further Comments
The total number of floating-point operations is approximately $\frac{1}{3}{n}^{3}$.
A call to f07wdc may be followed by calls to the functions: