Fit
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 
, 
, ... , 
, 
, 
, ... , 
, ... 
, 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 
, 
, ... 
, 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[
, 
, ... 
, 
1, x, x^2
, x] gives a quadratic fit to a sequence of values 
. The result is of the form 
+ 
x + 
x^2, where the 
are real numbers. The successive values of x needed to obtain the 
are assumed to be 1, 2, ... .
Fit[
, 
, 
, 
, ... 
, 
1, x, x^2
, x] does a quadratic fit, assuming a sequence of x values 
.
Fit[
, 
, 
, ... 
, 
1, x, y
, 
x, y
] finds a fit of the form 
+ 
x + 
y.
Fit always finds the linear combination of the functions in the list forms 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.
See The Mathematica Book on the web: Section 1.6.6 and Section 3.8.1.
Implementation Notes: see Section A.9.4.
See also: Interpolation, InterpolatingPolynomial, Solve, FindMinimum.
Further Examples
