SumSquaredErrors Command
- SumSquaredErrors( <List of Points>, <Function> )
-
Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.
If we have a list of points L={(1, 2), (3, 5),(2, 2), (5, 2), (5, 5)} and have calculated for example:
f(x)=FitPoly(L,1) and g(x)=FitPoly(L,2). SumSquaredErrors(L,f) yields 9 and
SumSquaredErrors(L,g) yields 6.99, and therefore we can see, that g(x) offers the best fit, in the sense of
the least sum of squared errors (Gauss).