| Calling Sequence | ExpFit2(y,x)
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| Parameters |
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| Return Type | [a, b, sumsq] | ||||||||||||
| Synopsis | Compute the least squares fit of the type y[i] ~ a * exp(b * x[i]). sumsq is the sum of squares of the approximation errors. | ||||||||||||
| 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] > ExpFit2(y,x); [0.2771, 0.6677, 0.00586200] | ||||||||||||
| See also | ExpFit, LinearRegression, Stat | ||||||||||||