/usr/include/simgear/math/leastsqs.hxx is in libsimgear-dev 3.4.0-3.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 | /**
* \file leastsqs.hxx
* Implements a simple linear least squares best fit routine.
*/
// Written by Curtis Olson, started September 1997.
//
// Copyright (C) 1997 Curtis L. Olson - http://www.flightgear.org/~curt
//
// This library is free software; you can redistribute it and/or
// modify it under the terms of the GNU Library General Public
// License as published by the Free Software Foundation; either
// version 2 of the License, or (at your option) any later version.
//
// This library 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
// Library General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
//
// $Id$
#ifndef _LEASTSQS_H
#define _LEASTSQS_H
#ifndef __cplusplus
# error This library requires C++
#endif
/**
Classical least squares fit:
\f[
y = b_0 + b_1 * x
\f]
\f[
b_1 = \frac{n * \sum_0^{i-1} (x_i*y_i) - \sum_0^{i-1} x_i* \sum_0^{i-1} y_i}
{n*\sum_0^{i-1} x_i^2 - (\sum_0^{i-1} x_i)^2}
\f]
\f[
b_0 = \frac{\sum_0^{i-1} y_i}{n} - b_1 * \frac{\sum_0^{i-1} x_i}{n}
\f]
*/
void least_squares(double *x, double *y, int n, double *m, double *b);
/**
* Incrimentally update existing values with a new data point.
*/
void least_squares_update(double x, double y, double *m, double *b);
/**
@return the least squares error:.
\f[
\frac{(y_i - \hat{y}_i)^2}{n}
\f]
*/
double least_squares_error(double *x, double *y, int n, double m, double b);
/**
@return the maximum least squares error.
\f[
(y_i - \hat{y}_i)^2
\f]
*/
double least_squares_max_error(double *x, double *y, int n, double m, double b);
#endif // _LEASTSQS_H
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