| 1 | /* -*-c-*- |
| 2 | * |
| 3 | * Simple linear regression |
| 4 | * |
| 5 | * (c) 2023 Straylight/Edgeware |
| 6 | */ |
| 7 | |
| 8 | /*----- Licensing notice --------------------------------------------------* |
| 9 | * |
| 10 | * This file is part of the mLib utilities library. |
| 11 | * |
| 12 | * mLib is free software: you can redistribute it and/or modify it under |
| 13 | * the terms of the GNU Library General Public License as published by |
| 14 | * the Free Software Foundation; either version 2 of the License, or (at |
| 15 | * your option) any later version. |
| 16 | * |
| 17 | * mLib is distributed in the hope that it will be useful, but WITHOUT |
| 18 | * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or |
| 19 | * FITNESS FOR A PARTICULAR PURPOSE. See the GNU Library General Public |
| 20 | * License for more details. |
| 21 | * |
| 22 | * You should have received a copy of the GNU Library General Public |
| 23 | * License along with mLib. If not, write to the Free Software |
| 24 | * Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, |
| 25 | * USA. |
| 26 | */ |
| 27 | |
| 28 | /*----- Header files ------------------------------------------------------*/ |
| 29 | |
| 30 | #include <assert.h> |
| 31 | #include <math.h> |
| 32 | |
| 33 | #include "linreg.h" |
| 34 | |
| 35 | /*----- Main code ---------------------------------------------------------*/ |
| 36 | |
| 37 | /* --- @linreg_init@ --- * |
| 38 | * |
| 39 | * Arguments: @struct linreg *lr@ = linear regression state |
| 40 | * |
| 41 | * Returns: --- |
| 42 | * |
| 43 | * Use: Initializes a linear-regression state ready for use. |
| 44 | */ |
| 45 | |
| 46 | void linreg_init(struct linreg *lr) |
| 47 | { |
| 48 | lr->sum_x = lr->sum_x2 = lr->sum_y = lr->sum_y2 = lr->sum_x_y = 0.0; |
| 49 | lr->n = 0; |
| 50 | } |
| 51 | |
| 52 | /* --- @linreg_update@ --- * |
| 53 | * |
| 54 | * Arguments: @struct linreg *lr@ = linear regression state |
| 55 | * @double x, y@ = point coordinates |
| 56 | * |
| 57 | * Returns: --- |
| 58 | * |
| 59 | * Use: Informs the linear regression machinery of a point. |
| 60 | * |
| 61 | * Note that the state size is constant, and independent of the |
| 62 | * number of points. |
| 63 | */ |
| 64 | |
| 65 | void linreg_update(struct linreg *lr, double x, double y) |
| 66 | { |
| 67 | lr->sum_x += x; lr->sum_x2 += x*x; lr->sum_x_y += x*y; |
| 68 | lr->sum_y += y; lr->sum_y2 += y*y; |
| 69 | lr->n++; |
| 70 | } |
| 71 | |
| 72 | /* --- @linreg_fit@ --- * |
| 73 | * |
| 74 | * Arguments: @const struct linreg *lr@ = linear regression state |
| 75 | * @double *m_out, *c_out, *r_out@ = where to write outputs |
| 76 | * |
| 77 | * Returns: --- |
| 78 | * |
| 79 | * Use: Compute the best-fit line through the previously-specified |
| 80 | * points. The line has the equation %$y = m x + c$%; %$m$% and |
| 81 | * %$c$% are written to @*m_out@ and @*c_out@ respectively, and |
| 82 | * the correlation coefficient %$r$% is written to @*r_out@. |
| 83 | * Any (or all, but that would be useless) of the output |
| 84 | * pointers may be null to discard that result. |
| 85 | * |
| 86 | * At least one point must have been given. |
| 87 | */ |
| 88 | |
| 89 | void linreg_fit(const struct linreg *lr, |
| 90 | double *m_out, double *c_out, double *r_out) |
| 91 | { |
| 92 | double E_X, E_X2, E2_X, E_X_Y, E_Y, E_Y2, E2_Y, n; |
| 93 | double cov_X_Y, var_X, var_Y, m; |
| 94 | assert(lr->n); |
| 95 | |
| 96 | n = lr->n; E_X_Y = lr->sum_x_y/n; |
| 97 | E_X = lr->sum_x/n; E_X2 = lr->sum_x2/n; E2_X = E_X*E_X; |
| 98 | E_Y = lr->sum_y/n; E_Y2 = lr->sum_y2/n; E2_Y = E_Y*E_Y; |
| 99 | |
| 100 | cov_X_Y = E_X_Y - E_X*E_Y; var_X = E_X2 - E2_X; var_Y = E_Y2 - E2_Y; |
| 101 | |
| 102 | m = cov_X_Y/var_X; |
| 103 | if (m_out) *m_out = m; |
| 104 | if (c_out) *c_out = E_Y - m*E_X; |
| 105 | if (r_out) *r_out = cov_X_Y/sqrt(var_X*var_Y); |
| 106 | } |
| 107 | |
| 108 | /*----- That's all, folks -------------------------------------------------*/ |