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51 lines
1.0 KiB
51 lines
1.0 KiB
/*Curve fitting problem by Least Squares
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Nigel_Galloway@operamail.com
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October 1st., 2007
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*/
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set Sample;
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param Sx {z in Sample};
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param Sy {z in Sample};
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var X;
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var Y;
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var Ex{z in Sample};
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var Ey{z in Sample};
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/* sum of variances is zero for Sx*/
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variencesX{z in Sample}: X + Ex[z] = Sx[z];
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zumVariancesX: sum{z in Sample} Ex[z] = 0;
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/* sum of variances is zero for Sy*/
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variencesY{z in Sample}: Y + Ey[z] = Sy[z];
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zumVariancesY: sum{z in Sample} Ey[z] = 0;
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solve;
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param b1 := (sum{z in Sample} Ex[z]*Ey[z])/(sum{z in Sample} Ex[z]*Ex[z]);
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printf "\nbest linear fit is:\n\ty = %f %s %fx\n\n", Y-b1*X, if b1 < 0 then "-" else "+", abs(b1);
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data;
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param:
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Sample: Sx Sy :=
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1 0 1
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2 0.5 0.9
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3 1 0.7
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4 1.5 1.5
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5 1.9 2
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6 2.5 2.4
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7 3 3.2
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8 3.5 2
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9 4 2.7
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10 4.5 3.5
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11 5 1
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12 5.5 4
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13 6 3.6
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14 6.6 2.7
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15 7 5.7
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16 7.6 4.6
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17 8.5 6
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18 9 6.8
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19 10 7.3
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;
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end;
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