Least Squares Regression Line

The least squares regression line is a line in the form of "y = a + b * x" that best fits a data set (time series).

The least squares regression is the most used modeling technique. It is mainly used to predict the future value of the analyzed time series.

Example:
a = RegLineLeastSquares(close,20);

The above instruction calculates, for each trading bar, the least squares regression line of the close series based on the previous 20 bars.

Note that this function allows you to use dynamic lookback period.

b = barssince(cross(close, sma(30)));
a = RegLineLeastSquares(close, b);

Calculates the least squares regression line using data starting from bar where the close price crossed above its 30-bar simple moving average.

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