File:Regression lineaire abscisses.svg
Summary
| Description |
English: Illustration of least squares fitting. The data (red dots) are at co-ordinates (1,6), (2,5), (3,7) and (4,10). A linear approximation is obtained using least-squares estimation for the horizontal offset (blue line). Created using Scilab, modified with Inkscape.
Français : Illustration de la régression linéaire par la méthode des moindres carrés. Les données (points rouges) ont pour coordonnées (1 ; 6), (2 ; 5), (3 ; 7) et (4 ; 10). On effectue une régression linéaire en considérant les écarts en abscisse (ligne bleue). Réalisé avec Scilab, modifié avec Inkscape. |
| Date | (UTC) |
| Source |
This file was derived from: Linear least squares example2.svg: Category:Derivative versions |
| Author |
|
| This is a retouched picture, which means that it has been digitally altered from its original version. Modifications: redrawn from the same data set, with a different algorithm and language. The original can be viewed here: Linear least squares example2.svg: |
Scilab source
Category:Images with Scilab code// Données
X = 1:4;
Y = [6, 5, 7, 10];
// régression
[a, b, sigma] = reglin(Y, X);
// points projetés sur la droite
X1 = a*Y + b;
// droite de régression
y1 = 4; x1 = a*y1 + b;
y2 = 10.25; x2 = a*y2 + b;
// tracé
clf;
couleurs = [get(sdf(), 'color_map') ; 0.75, 0.75, 0.75];
xset('colormap', couleurs);
xsegs([X ; X1], [Y ; Y], 14) // segments
h1 = gce();
h1.thickness = 2;
xpoly([x1, x2], [y1, y2]) // droite de régression
h2 = gce();
h2.thickness = 2;
h2.foreground = 2;
plot(X, Y, 'ok') // points
h3 = gce();
h3.children.mark_background = 5;
axe = gca();
axe.data_bounds = [0, 4 ; 5, 10.25];
axe.grid = [33, 33];
axe.tight_limits = 'on';
axe.isoview = 'on';
xtitle(' ', 'x', 'y')
Licensing
I, the copyright holder of this work, hereby publish it under the following licenses:
This file is licensed under the Creative Commons Attribution-Share Alike 3.0 Unported license.
- You are free:
- to share – to copy, distribute and transmit the work
- to remix – to adapt the work
- Under the following conditions:
- attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- share alike – If you remix, transform, or build upon the material, you must distribute your contributions under the same or compatible license as the original.
| Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled GNU Free Documentation License. |
You may select the license of your choice.
Original upload log
This image is a derivative work of the following images:
- File:Linear_least_squares_example2.svg licensed with Cc-by-sa-3.0, GFDL
- 2011-06-10T03:35:22Z Krishnavedala 279x274 (51647 Bytes) {{Information |Description ={{en|1=Illustration of [[:w:Linear_least_squares_(mathematicsleast squares fitting]]. The data (red dots) are at co-ordinates (1,6), (2,5), (3,7) and (4,10). A linear approximation is obtained u
Uploaded with derivativeFX Category:Uploaded with derivativeFX
Category:Linear regression
Category:CC-BY-SA-3.0
Category:Derivative versions
Category:Files by User:cdang
Category:GFDL
Category:Images with Scilab code
Category:License migration redundant
Category:Linear regression
Category:SVG retouched pictures
Category:Self-published work
Category:Unspec New SVG created with Inkscape
Category:Unspec SVG created with Inkscape
Category:Uploaded with derivativeFX
