Difference between revisions of "SumSquaredErrors Command"
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| − | <noinclude>{{Manual Page|version= | + | <noinclude>{{Manual Page|version=5.0}}</noinclude>{{command|statistics}} |
| − | {{command|statistics}} | + | ;SumSquaredErrors( <List of Points>, <Function> ) |
| − | ;SumSquaredErrors | ||
: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. | :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. | ||
| − | {{example|1= If we have a list of points | + | :{{example|1= If we have a list of points <code><nowiki>L={(1, 2), (3, 5),(2, 2), (5, 2), (5, 5)}</nowiki></code> and have calculated for example: <code>f(x)=FitPoly(L,1)</code> and <code>g(x)=FitPoly(L,2)</code>. <code>SumSquaredErrors(L,f)</code> yields ''9'' and <code>SumSquaredErrors(L,g)</code> 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).}} |
Latest revision as of 10:24, 12 October 2017
- 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.
- Example: 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)andg(x)=FitPoly(L,2).SumSquaredErrors(L,f)yields 9 andSumSquaredErrors(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).
