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Fit[data, funs, vars]
finds a least-squares fit to a list of data as a linear combination of the functions funs of variables vars.
  • The data can have the form {{x_1,y_1,… ,f_1},{x_2,y_2,… ,f_2},…}, where the number of coordinates x,y,… is equal to the number of variables in the list vars.
  • The data can also be of the form {f_1,f_2,…}, with a single coordinate assumed to take values 1, 2, ....
  • The argument funs can be any list of functions that depend only on the objects vars.
  • Fit[{f1, f2, ...}, {1, x, x^2}, x] gives a quadratic fit to a sequence of values fi. The result is of the form a0+a1x+a2x^2, where the ai are real numbers. The successive values of x needed to obtain the fi are assumed to be 1, 2, ... .  »
  • Fit[{{x1, f1}, {x2, f2}, ...}, {1, x, x^2}, x] does a quadratic fit, assuming a sequence of x values xi.  »
  • Fit[{{x1, y1, f1}, ...}, {1, x, y}, {x, y}] finds a fit of the form a0+a1x+a2y.  »
  • Fit always finds the linear combination of the functions in the list funs that minimizes the sum of the squares of deviations from the values fi.  »
  • Exact numbers given as input to Fit are converted to approximate numbers with machine precision.  »
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