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# NAG Toolbox: nag_matop_real_vband_posdef_fac (f01mc)

## Purpose

nag_matop_real_vband_posdef_fac (f01mc) computes the Cholesky factorization of a real symmetric positive definite variable-bandwidth matrix.

## Syntax

[al, d, ifail] = f01mc(a, nrow, 'n', n, 'lal', lal)
[al, d, ifail] = nag_matop_real_vband_posdef_fac(a, nrow, 'n', n, 'lal', lal)

## Description

nag_matop_real_vband_posdef_fac (f01mc) determines the unit lower triangular matrix L$L$ and the diagonal matrix D$D$ in the Cholesky factorization A = LDLT$A=LD{L}^{\mathrm{T}}$ of a symmetric positive definite variable-bandwidth matrix A$A$ of order n$n$. (Such a matrix is sometimes called a ‘sky-line’ matrix.)
The matrix A$A$ is represented by the elements lying within the envelope of its lower triangular part, that is, between the first nonzero of each row and the diagonal (see Section [Example] for an example). The width nrow(i)${\mathbf{nrow}}\left(i\right)$ of the i$i$th row is the number of elements between the first nonzero element and the element on the diagonal, inclusive. Although, of course, any matrix possesses an envelope as defined, this function is primarily intended for the factorization of symmetric positive definite matrices with an average bandwidth which is small compared with n$n$ (also see Section [Further Comments]).
The method is based on the property that during Cholesky factorization there is no fill-in outside the envelope.
The determination of L$L$ and D$D$ is normally the first of two steps in the solution of the system of equations Ax = b$Ax=b$. The remaining step, viz. the solution of LDLTx = b$LD{L}^{\mathrm{T}}x=b$, may be carried out using nag_linsys_real_posdef_vband_solve (f04mc).

## References

Jennings A (1966) A compact storage scheme for the solution of symmetric linear simultaneous equations Comput. J. 9 281–285
Wilkinson J H and Reinsch C (1971) Handbook for Automatic Computation II, Linear Algebra Springer–Verlag

## Parameters

### Compulsory Input Parameters

1:     a(lal) – double array
lal, the dimension of the array, must satisfy the constraint lalnrow(1) + nrow(2) + + nrow(n)${\mathbf{lal}}\ge {\mathbf{nrow}}\left(1\right)+{\mathbf{nrow}}\left(2\right)+\dots +{\mathbf{nrow}}\left(n\right)$.
The elements within the envelope of the lower triangle of the positive definite symmetric matrix A$A$, taken in row by row order. The following code assigns the matrix elements within the envelope to the correct elements of the array:
k = 0;
for i = 1:n
for j = i-nrow(i)+1:i
k = k + 1;
a(k) = matrix(i,j);
end
end
2:     nrow(n) – int64int32nag_int array
n, the dimension of the array, must satisfy the constraint n1${\mathbf{n}}\ge 1$.
nrow(i)${\mathbf{nrow}}\left(i\right)$ must contain the width of row i$i$ of the matrix A$A$, i.e., the number of elements between the first (leftmost) nonzero element and the element on the diagonal, inclusive.
Constraint: 1nrow(i)i$1\le {\mathbf{nrow}}\left(\mathit{i}\right)\le \mathit{i}$, for i = 1,2,,n$\mathit{i}=1,2,\dots ,n$.

### Optional Input Parameters

1:     n – int64int32nag_int scalar
Default: The dimension of the array nrow.
n$n$, the order of the matrix A$A$.
Constraint: n1${\mathbf{n}}\ge 1$.
2:     lal – int64int32nag_int scalar
Default: The dimension of the array a.
The dimension of the arrays a and al as declared in the (sub)program from which nag_matop_real_vband_posdef_fac (f01mc) is called.
Constraint: lalnrow(1) + nrow(2) + + nrow(n)${\mathbf{lal}}\ge {\mathbf{nrow}}\left(1\right)+{\mathbf{nrow}}\left(2\right)+\dots +{\mathbf{nrow}}\left(n\right)$.

None.

### Output Parameters

1:     al(lal) – double array
The elements within the envelope of the lower triangular matrix L$L$, taken in row by row order. The envelope of L$L$ is identical to that of the lower triangle of A$A$. The unit diagonal elements of L$L$ are stored explicitly. See also Section [Further Comments].
2:     d(n) – double array
The diagonal elements of the diagonal matrix D$D$. Note that the determinant of A$A$ is equal to the product of these diagonal elements. If the value of the determinant is required it should not be determined by forming the product explicitly, because of the possibility of overflow or underflow. The logarithm of the determinant may safely be formed from the sum of the logarithms of the diagonal elements.
3:     ifail – int64int32nag_int scalar
${\mathrm{ifail}}={\mathbf{0}}$ unless the function detects an error (see [Error Indicators and Warnings]).

## Error Indicators and Warnings

Errors or warnings detected by the function:

Cases prefixed with W are classified as warnings and do not generate an error of type NAG:error_n. See nag_issue_warnings.

ifail = 1${\mathbf{ifail}}=1$
 On entry, n < 1${\mathbf{n}}<1$, or for some i$i$, nrow(i) < 1${\mathbf{nrow}}\left(i\right)<1$ or nrow(i) > i${\mathbf{nrow}}\left(i\right)>i$, or lal < nrow(1) + nrow(2) + … + nrow(n)${\mathbf{lal}}<{\mathbf{nrow}}\left(1\right)+{\mathbf{nrow}}\left(2\right)+\dots +{\mathbf{nrow}}\left({\mathbf{n}}\right)$.
ifail = 2${\mathbf{ifail}}=2$
A$A$ is not positive definite, or this property has been destroyed by rounding errors. The factorization has not been completed.
W ifail = 3${\mathbf{ifail}}=3$
A$A$ is not positive definite, or this property has been destroyed by rounding errors. The factorization has not been completed.

## Accuracy

If ${\mathbf{ifail}}={\mathbf{0}}$ on exit, then the computed L$L$ and D$D$ satisfy the relation LDLT = A + F$LD{L}^{\mathrm{T}}=A+F$, where
 ‖F‖2 ≤ km2ε × max aii i
$‖F‖2 ≤ km2 ε × maxi aii$
and
 ‖F‖2 ≤ km2 ε × ‖A‖2 , $‖F‖2 ≤ km2 ε × ‖A‖2 ,$
where k$k$ is a constant of order unity, m$m$ is the largest value of nrow(i)${\mathbf{nrow}}\left(i\right)$, and ε$\epsilon$ is the machine precision. See pages 25–27 and 54–55 of Wilkinson and Reinsch (1971).

## Further Comments

The time taken by nag_matop_real_vband_posdef_fac (f01mc) is approximately proportional to the sum of squares of the values of nrow(i)${\mathbf{nrow}}\left(i\right)$.
The distribution of row widths may be very non-uniform without undue loss of efficiency. Moreover, the function has been designed to be as competitive as possible in speed with functions designed for full or uniformly banded matrices, when applied to such matrices.

## Example

function nag_matop_real_vband_posdef_fac_example
a = [1;
2;
5;
3;
13;
16;
5;
14;
18;
8;
55;
24;
17;
77];
nrow = [int64(1);2;2;1;5;3];
[al, d, ifail] = nag_matop_real_vband_posdef_fac(a, nrow)

al =

1.0000
2.0000
1.0000
3.0000
1.0000
1.0000
5.0000
4.0000
1.5000
0.5000
1.0000
1.5000
5.0000
1.0000

d =

1
1
4
16
1
16

ifail =

0

function f01mc_example
a = [1;
2;
5;
3;
13;
16;
5;
14;
18;
8;
55;
24;
17;
77];
nrow = [int64(1);2;2;1;5;3];
[al, d, ifail] = f01mc(a, nrow)

al =

1.0000
2.0000
1.0000
3.0000
1.0000
1.0000
5.0000
4.0000
1.5000
0.5000
1.0000
1.5000
5.0000
1.0000

d =

1
1
4
16
1
16

ifail =

0

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Chapter Introduction
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