Description: A Function that returns a linear regression channel using (X,Y) vector points.
Inputs: _X: Array containing x data points.¹ _Y: Array containing y data points.¹
Note: ¹: _X and _Y size must match.
Outputs: _predictions: Array with adjusted _Y values at _X. _max_dev: Max deviation from the mean. _min_dev: Min deviation from the mean. _stdev/_sizeX: Average deviation from the mean.
Just wanted to note, that there are some arrays that don't necessarily start with index 0 (some have values starting at index 2 for example). So when using this function on those arrays, one gets NaN for the outputs. Adding nz() to the arrays in the calculations helps resolve that problem:
Just wanted to note, that there are some arrays that don't necessarily start with index 0 (some have values starting at index 2 for example). So when using this function on those arrays, one gets NaN for the outputs. Adding nz() to the arrays in the calculations helps resolve that problem:
_sumXY := _sumXY + (nz(_Xi) * nz(_Yi))
_sumX2 := _sumX2 + pow(nz(_Xi), 2)
_sumY2 := _sumY2 + pow(nz(_Yi), 2)
Very helpful script.