Difference between revisions of "SumSquaredErrors Command"

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<noinclude>{{Manual Page|version=4.2}}</noinclude>
 
<noinclude>{{Manual Page|version=4.2}}</noinclude>
 
{{command|statistics}}
 
{{command|statistics}}
;SumSquaredErrors[ <List of Points>, <Function> ]
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;SSumSquaredErrors[ <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.
 
: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: L={A,B,C,D,E}  and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code>, then it is possible to decide which of the two functions offers the best fit, in the sense of the least sum of squared errors (Gauss), by comparing: <code>sse_f=SumSquaredErrors[L,f]</code> and <code>sse_g=SumSquaredErrors[L,g]</code>.}}
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:{{example|1= If we have a list of points: L={A,B,C,D,E}  and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code>, then it is possible to decide which of the two functions offers the best fit, in the sense of the least sum of squared errors (Gauss), by comparing: <code>sse_f=SumSquaredErrors[L,f]</code> and <code>sse_g=SumSquaredErrors[L,g]</code>.}}

Revision as of 13:58, 16 July 2013



SSumSquaredErrors[ <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={A,B,C,D,E} and have calculated for example: f(x)=FitPoly[L,1] and g(x)=FitPoly[L,2], then it is possible to decide which of the two functions offers the best fit, in the sense of the least sum of squared errors (Gauss), by comparing: sse_f=SumSquaredErrors[L,f] and sse_g=SumSquaredErrors[L,g].
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