| Calling Sequence | ExpFit(y,x)
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| Parameters |
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| Return Type | [a,b,c,sumsq] | ||||||||||||
| Synopsis | Compute a least squares fit of the type: | ||||||||||||
y[i] ~ a + b * exp(c*x[i]) | |||||||||||||
where a,b and c are the parameters of the approximation and sumsq is the sum of the squares of the errors of the approximation. | |||||||||||||
| Examples | > x := [1,2,3,4,5]; x := [1, 2, 3, 4, 5] > y := [0.49, 1.02, 2.1, 4.01, 7.8]; y := [0.4900, 1.0200, 2.1000, 4.0100, 7.8000] > ExpFit(y,x); [-0.1014, 0.3113, 0.6467, 0.00204305] | ||||||||||||
| See also | ExpFit2, LinearRegression, Stat | ||||||||||||