(Engine-Level Function)
| Description: | Returns the coefficient of determination (i.e. r2) for a linear curve fit. This number gives a measure of how accurate the curve fit is. |
| Returns: | Numeric |
Usage:  |
Script or steady state. |
| Function Groups: | Generic Math |
| Related to: | FitOffset | FitSlope |
| Format: |
FitR2(XarrayElem, YarrayElem, N) |
| Parameters: |
| XArrayElem |
| Required. Any array element giving the starting point in the array of X coordinates of the input data set. The subscript for the array may be any numeric expression. If processing a multidimensional array, the usual rules apply to decide which dimension should be used. |
| YArrayElem |
| Required. Any array element giving the starting point in the array of Y coordinates of the input data set. The subscript for the array may be any numeric expression. If processing a multidimensional, the usual rules apply to decide which dimension should be used. |
| N |
| Required. Any numeric expression giving the number of data points to use from the arrays given by the first two parameters. If N extends past the upper bound of the lowest array dimension, this computation will "wrap-around" and resume at element 0, until N elements have been processed. |
| Comments: | This function returns a number indicating how close a fit the data are to a line. If an element of either array is invalid, then that X-Y pair is not included in the computation. If the result is 0, there is no linear relationship at all between the array of X values and the array of Y values. If the result is 1, the fit is perfect. The result may be any value in the range of 0 to 1. This function can be used in conjunction with the other linear regression functions. |
Example:
Assume that 2 arrays exist such that X = {0, 1, 2, 3} and Y = {1, 3, 5, 7 }, and both arrays' subscripts start at 0
Determination = FitR2(X[0] { Starting X element },
Y[0] { Starting Y element },
4 { Number of elements to process });
The value of determination will be set to 1 (a perfect fit).
