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. The data can have the form {{x_1, ...

When you have numerical data, it is often convenient to find a simple formula that approximates it. For example, you can try to "fit" a line or curve through the points in ...

There are many situations where one wants to find a formula that best fits a given set of data. One way to do this in Mathematica is to use Fit. Basic linear fitting. Here is ...

LeastSquares — solve an exact or approximate least-squares problem, PseudoInverse — pseudoinverse of a square or rectangular matrix, Norm — matrix and vector p-norms, ...

NormFunction is an option for functions such as FindFit and NDSolve which gives a function to be minimized in generating results.

FindCurvePath[{{x_1, y_1}, {x_2, y_2}, ...}] gives an ordering of the {x_i, y_i} that corresponds to one or more smooth curves.

Version 6.0 added a collection of carefully optimized functions to Mathematica's powerful arsenal of numerical handling capabilities.

Compiled is an option for various numerical and plotting functions which specifies whether the expressions they work with should automatically be compiled.

Gradient is an option for FindMinimum and related functions that specifies the gradient vector to assume for the function being extremized.

NonlinearFit is replaced by FindFit. NonlinearRegress functionality is now available using the built-in function NonlinearModelFit.