Difference between revisions of "SumSquaredErrors Command"
From GeoGebra Manual
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;SumSquaredErrors[ <List of Points>, <Function> ] | ;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. | :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: f(x)=RegPoly[L,1] and g(x)=RegPoly[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].}} | ||
Revision as of 12:30, 9 December 2011
- 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={A,B,C,D,E} and have calculated for example: f(x)=RegPoly[L,1] and g(x)=RegPoly[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].
