Least-squares line fitting: Difference between revisions
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This little JXSGraph application finds the line - described by homogeneous coordinates [a,b,1] - that minimizes | |||
:<math> \sum_{i=1}^n (a_ix_i+b_iy_i+1)^2.</math> | |||
<jsxgraph width="600" height="600"> | <jsxgraph width="600" height="600"> | ||
var brd = JXG.JSXGraph.initBoard('jxgbox',{boundingbox:[-5,5,5,-5], keepaspectratio:true}); | var brd = JXG.JSXGraph.initBoard('jxgbox',{boundingbox:[-5,5,5,-5], keepaspectratio:true}); | ||
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// points from the line. | // points from the line. | ||
brd.suspendUpdate(); | brd.suspendUpdate(); | ||
for (i=0;i< | for (i=0;i<1000;i++) { | ||
xr = 10*(Math.random()-0.5); | xr = 10*(Math.random()-0.5); | ||
yr = 0.3*xr+delta*(Math.random()-0.5) +1.0; | yr = 0.3*xr+delta*(Math.random()-0.5) +1.0; | ||
Revision as of 19:39, 5 November 2010
This little JXSGraph application finds the line - described by homogeneous coordinates [a,b,1] - that minimizes
- [math]\displaystyle{ \sum_{i=1}^n (a_ix_i+b_iy_i+1)^2. }[/math]
