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java.lang.Object | +----org.netlib.lapack.Dgelsx
Following is the description from the original Fortran source. For each array argument, the Java version will include an integer offset parameter, so the arguments may not match the description exactly. Contact seymour@cs.utk.edu with any questions.* .. * * Purpose * ======= * * DGELSX computes the minimum-norm solution to a real linear least * squares problem: * minimize || A * X - B || * using a complete orthogonal factorization of A. A is an M-by-N * matrix which may be rank-deficient. * * Several right hand side vectors b and solution vectors x can be * handled in a single call; they are stored as the columns of the * M-by-NRHS right hand side matrix B and the N-by-NRHS solution * matrix X. * * The routine first computes a QR factorization with column pivoting: * A * P = Q * [ R11 R12 ] * [ 0 R22 ] * with R11 defined as the largest leading submatrix whose estimated * condition number is less than 1/RCOND. The order of R11, RANK, * is the effective rank of A. * * Then, R22 is considered to be negligible, and R12 is annihilated * by orthogonal transformations from the right, arriving at the * complete orthogonal factorization: * A * P = Q * [ T11 0 ] * Z * [ 0 0 ] * The minimum-norm solution is then * X = P * Z' [ inv(T11)*Q1'*B ] * [ 0 ] * where Q1 consists of the first RANK columns of Q. * * Arguments * ========= * * M (input) INTEGER * The number of rows of the matrix A. M >= 0. * * N (input) INTEGER * The number of columns of the matrix A. N >= 0. * * NRHS (input) INTEGER * The number of right hand sides, i.e., the number of * columns of matrices B and X. NRHS >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the M-by-N matrix A. * On exit, A has been overwritten by details of its * complete orthogonal factorization. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS) * On entry, the M-by-NRHS right hand side matrix B. * On exit, the N-by-NRHS solution matrix X. * If m >= n and RANK = n, the residual sum-of-squares for * the solution in the i-th column is given by the sum of * squares of elements N+1:M in that column. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,M,N). * * JPVT (input/output) INTEGER array, dimension (N) * On entry, if JPVT(i) .ne. 0, the i-th column of A is an * initial column, otherwise it is a free column. Before * the QR factorization of A, all initial columns are * permuted to the leading positions; only the remaining * free columns are moved as a result of column pivoting * during the factorization. * On exit, if JPVT(i) = k, then the i-th column of A*P * was the k-th column of A. * * RCOND (input) DOUBLE PRECISION * RCOND is used to determine the effective rank of A, which * is defined as the order of the largest leading triangular * submatrix R11 in the QR factorization with pivoting of A, * whose estimated condition number < 1/RCOND. * * RANK (output) INTEGER * The effective rank of A, i.e., the order of the submatrix * R11. This is the same as the order of the submatrix T11 * in the complete orthogonal factorization of A. * * WORK (workspace) DOUBLE PRECISION array, dimension * (max( min(M,N)+3*N, 2*min(M,N)+NRHS )), * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * ===================================================================== * * .. Parameters ..
Dgelsx()
dgelsx(int, int, int, double[], int, int, double[], int, int, int[], int, double, intW, double[], int, intW)
Dgelsx
public Dgelsx()
dgelsx
public static void dgelsx(int m,
int n,
int nrhs,
double a[],
int _a_offset,
int lda,
double b[],
int _b_offset,
int ldb,
int jpvt[],
int _jpvt_offset,
double rcond,
intW rank,
double work[],
int _work_offset,
intW info)
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