File:Regression lineaire ordonnees orthogonal.svg
Original file (SVG file, nominally 317 × 384 pixels, file size: 44 KB)
Captions
Summary[edit]
DescriptionRegression lineaire ordonnees orthogonal.svg |
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 of the vertical offset (plain blue line) and of the perpendicular offset (total least squares, dashed 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 ordonnée (ligne bleue continue) et orthogonaux (moindres carrés totaux, trait pointillé bleu). Réalisé avec Scilab, modifié avec Inkscape. |
Date | (UTC) |
Source |
This file was derived from: Linear least squares example2.svg: |
Author |
|
This is a retouched picture, which means that it has been digitally altered from its original version. Modifications: redrawn with Scilab, with two different algorithms. The original can be viewed here: Linear least squares example2.svg: . Modifications made by Cdang.
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Scilab source
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 horizontale
[a, b, sigma] = reglin(Y, X);
// régression verticale
[aa, bb, sigma] = reglin(X, Y);
// régression orthogonale
Ainit = [0, 1];
function [e] = resorth(A, X, Y)
e = 1/(1 + A(2)^2)*(Y - A(1) - A(2)*X).^2
endfunction
[S, Aopt] = leastsq(list(resorth, X', Y'), Ainit);
// points projetés sur la droite
Xh = a*Y + b;
Yv = aa*X + bb;
normdo = sqrt(1 + Aopt(2)^2);
distcurv = (1/normdo)*(X + Aopt(2)*(Y - Aopt(1)));
Xorth = (1/normdo)*distcurv;
Yorth = Aopt(1) + (Aopt(2)/normdo)*distcurv;
// droite de régression verticale
xx1 = (y1 - bb)/aa;
xx2 = (y2 - bb)/aa;
// droite de régression orthogonale
xxx1 = (y1 - Aopt(1))/Aopt(2);
xxx2 = (y2 - Aopt(1))/Aopt(2);
// tracé
clf;
couleurs = [get(sdf(), 'color_map') ; 0.75, 0.75, 0.75];
xset('colormap', couleurs);
xsegs([X ; X], [Y ; Yv], 14) // segments verticaux
h2 = gce();
h2.thickness = 2;
xsegs([X ; Xorth], [Y ; Yorth], 14) // segments orthogonaux
h2 = gce();
h2.line_style = 2;
xpoly([xx1, xx2], [y1, y2]) // droite de régression verticale
h3 = gce();
h3.thickness = 2;
h3.foreground = 2;
xpoly([xxx1, xxx2], [y1, y2]) // droite de régression orthogonale
h5 = gce();
h5.line_style = 2;
h5.foreground = 2;
plot(X, Y, 'ok') // points
h5 = gce();
h5.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]
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- 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.
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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.http://www.gnu.org/copyleft/fdl.htmlGFDLGNU Free Documentation Licensetruetrue |
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 | |
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current | 07:43, 5 April 2013 | 317 × 384 (44 KB) | Cdang (talk | contribs) | line styles inverted + G | |
15:09, 3 April 2013 | 317 × 384 (43 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 ... |
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Short title | Comparaison entre les régressions linéaires verticale et orthogonale |
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Width | 317.23727 |
Height | 383.6875 |