This is documentation for Mathematica 7, which was
based on an earlier version of the Wolfram Language.
 Curve Fitting & Approximate Functions Built into Mathematica are state-of-the-art constrained nonlinear fitting capabilities, conveniently accessed with models given directly in symbolic form. Mathematica also supports unique symbolic interpolating functions that can immediately be used throughout the system to efficiently represent approximate numerical functions. FindFit — find a general nonlinear fit, potentially including parameter constraints      Fit — linear least-squares fit to a list of symbolic functions LeastSquares — solution to a least-squares problem in matrix form      Interpolation — find an interpolation to data in any number of dimensions InterpolatingFunction — represent an approximate function to be evaluated repeatedly      InterpolatingPolynomial — construct a symbolic interpolating polynomial TUTORIALS Curve Fitting Statistical Model Analysis Approximate Functions and Interpolation Manipulating Numerical Data Unconstrained Optimization MORE ABOUT Statistics Data Transforms and Smoothing Statistical Model Fitting & Analysis Series Expansions Function Approximations Package Computational Geometry RELATED LINKS Demonstrations related to Curve Fitting & Approximate Functions (The Wolfram Demonstrations Project)