Abbreviation: LinXYReg StndErr
Category: Regression
Input Parameters:
| Name | Range | Default |
| X Axis | Close | |
| Y Axis | Close | |
| Regression Periods | Int >= 3 | 40 |
Calculation:
sqrt ( [n*sum(Y*Y) – sum(Y)*sum(Y) – [ [n*sum(X*Y) – sum(X)*sum(Y)] ^ 2 ] / [n*sum(X*X) – sum(X)*sum(X) ] ] / [n*(n-1)] )
where
sum(X*X) = sum of X*X over the last n periods
sum(Y*Y) = sum of Y*Y over the last n periods
sum(X*Y) = sum of X*Y over the last n periods
sum(X) = sum of X over the last n periods
sum(Y) = sum of Y over the last n periods
X = X Axis
Y = Y Axis
n = Regression Periods
Discussion:
Computes the standard error of estimate for the linear regression. The standard error of estimate is simply the standard deviation of the vertical distance between the points and the linear regression line. Note that the linear regression line is the straight line that provides the best fit to the X and Y points over the last n periods.