File:Regression lineaire abscisses.svg
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Size of this PNG preview of this SVG file: 317 × 384 pixels. Other resolutions: 198 × 240 pixels | 396 × 480 pixels | 634 × 768 pixels | 845 × 1,024 pixels | 1,691 × 2,048 pixels.
Original file (SVG file, nominally 317 × 384 pixels, file size: 41 KB)
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Summary[edit]
| 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:  |
| Author |
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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: . Modifications made by Cdang.
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This W3C-unspecified vector image was created with Inkscape .
Scilab source
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This media was created with Scilab, a free open-source software. Here is a listing of the Scilab source used to create this file. |
// 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[edit]
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.
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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[edit]
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
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| Date/Time | Thumbnail | Dimensions | User | Comment | |
|---|---|---|---|---|---|
| current | 07:42, 5 April 2013 | | 317 × 384 (41 KB) | Cdang (talk | contribs) | + G |
| 13:18, 3 April 2013 |  | 317 × 384 (40 KB) | Cdang (talk | contribs) | == {{int:filedesc}} == {{Information |Description={{en|1=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 l... |
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