Difference between revisions of "Fit Command"
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;Fit[<List of points>, <Function>] | ;Fit[<List of points>, <Function>] | ||
:Calculates a minimum squared error function to the points in the list. The Function must depend on one or more sliders, that are taken as start values of parameters to be optimized. The non-linear iteration might not converge, but adjusting the sliders to a better starting point might help. | :Calculates a minimum squared error function to the points in the list. The Function must depend on one or more sliders, that are taken as start values of parameters to be optimized. The non-linear iteration might not converge, but adjusting the sliders to a better starting point might help. | ||
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| + | {{note|1=Other point fitting commands are [[FitExp Command|FitExp]], [[FitGrowth Command|FitGrowth]], [[FitLine Command|FitLine]],[[FitLineX Command|FitLineX]], [[FitLog Command|FitLog]], [[FitLogistic Command|FitLogistic]], [[FitPoly Command|FitPoly]], [[FitPow Command|FitPow]] and [[FitSin Command|FitSin]].}} | ||
Revision as of 08:11, 30 January 2012
- Fit[ <List of Points>,<List of Functions> ]
- Calculates a linear combination of functions to the points in the list.
Example: With L={A,B,C,...}, f(x)=1, g(x)=x, h(x)=e^x, F={f,g,h}
the command
Fit[L,F] calculates a function of the form a + b x + c e^x to the points in the list.- Fit[<List of points>, <Function>]
- Calculates a minimum squared error function to the points in the list. The Function must depend on one or more sliders, that are taken as start values of parameters to be optimized. The non-linear iteration might not converge, but adjusting the sliders to a better starting point might help.
