Wolfram Language & System 10.4 (2016)|Legacy Documentation

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finds a leastsquares fit to a list of data as a linear combination of the functions funs of variables vars.


  • The data can have the form , where the number of coordinates , , is equal to the number of variables in the list vars.
  • The data can also be of the form , 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 . The result is of the form , where the are real numbers. The successive values of needed to obtain the are assumed to be 1, 2, . »
  • Fit[{{x1,f1},{x2,f2},},{1,x,x^2},x] does a quadratic fit, assuming a sequence of values . »
  • Fit[{{x1,y1,f1},},{1,x,y},{x,y}] finds a fit of the form . »
  • 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 . »
  • Exact numbers given as input to Fit are converted to approximate numbers with machine precision. »

ExamplesExamplesopen allclose all

Basic Examples  (1)Basic Examples  (1)

Here is some data:

Click for copyable input

Find the line that best fits the data:

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Find the quadratic that best fits the data:

Click for copyable input

Show the data with the two curves:

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Introduced in 1988