/* PSPP - a program for statistical analysis. Copyright (C) 2005 Free Software Foundation, Inc. This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see . */ #ifndef SWEEP_H #define SWEEP_H /* Find the least-squares estimate of b for the linear model: Y = Xb + Z where Y is an n-by-1 column vector, X is an n-by-p matrix of independent variables, b is a p-by-1 vector of regression coefficients, and Z is an n-by-1 normally-distributed random vector with independent identically distributed components with mean 0. This estimate is found via the sweep operator, which is a modification of Gauss-Jordan pivoting. References: Matrix Computations, third edition. GH Golub and CF Van Loan. The Johns Hopkins University Press. 1996. ISBN 0-8018-5414-8. Numerical Analysis for Statisticians. K Lange. Springer. 1999. ISBN 0-387-94979-8. Numerical Linear Algebra for Applications in Statistics. JE Gentle. Springer. 1998. ISBN 0-387-98542-5. */ /* The matrix A will be overwritten. In ordinary uses of the sweep operator, A will be the matrix __ __ |X'X X'Y| | | |Y'X Y'Y| -- -- X refers to the design matrix and Y to the vector of dependent observations. reg_sweep sweeps on the diagonal elements of X'X. The matrix A is assumed to be symmetric, so the sweep operation is performed only for the upper triangle of A. */ #include #include int reg_sweep (gsl_matrix *, int); #endif