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FilledSmallSquare FindFit[data, expr, pars, vars] finds numerical values of the parameters pars that make expr give a best fit to data as a function of vars.

FilledSmallSquare The data can have the form , , ... , , , , ... , , ... , where the number of coordinates x, y, ... is equal to the number of variables in the list vars.

FilledSmallSquare The data can also be of the form , , ... , with a single coordinate assumed to take values 1, 2, ... .

FilledSmallSquare FindFit returns a list of replacements for , , ... .

FilledSmallSquare The expression expr must yield a numerical value when pars and vars are all numerical.

FilledSmallSquare The expression expr can depend either linearly or nonlinearly on the .

FilledSmallSquare In the linear case, FindFit finds a globally optimal fit.

FilledSmallSquare In the nonlinear case, it finds in general only a locally optimal fit.

FilledSmallSquare FindFit[data, expr, , , , , ... , vars] starts the search for a fit with -> , -> , ... .

FilledSmallSquare FindFit by default finds a least-squares fit.

FilledSmallSquare The option NormFunction -> f specifies that the norm f[residual] should be minimized.

FilledSmallSquare The following options can be given:

FilledSmallSquare The default settings for AccuracyGoal and PrecisionGoal are WorkingPrecision/2.

FilledSmallSquare The settings for AccuracyGoal and PrecisionGoal specify the number of digits to seek in both the values of the parameters returned, and the value of the NormFunction.

FilledSmallSquare FindFit continues until either of the goals specified by AccuracyGoal or PrecisionGoal is achieved.

FilledSmallSquare Possible settings for Method are as for FindMinimum.

FilledSmallSquare See Section 1.6.6 and Section 3.8.2.

FilledSmallSquare Implementation Notes: see Section A.9.4.

FilledSmallSquare See also: FindMinimum, Fit, NMinimize, Interpolation.

FilledSmallSquare Related packages: Statistics`NonlinearFit`, Statistics`LinearRegression`.

FilledSmallSquare New in Version 5.0.

Further Examples