{_LinRegSlopeSFC - Linear Regression Slope Super Fast Calc
 by Alex Matulich, Unicorn Research Corporation, last updated 4/24/2004
 Derived from an algorithm developed by Bob Fulks and separately by
 Mark A. Simms (Index Options Group, 2002).
 Update 11/17/2002 (Bob Fulks): Re-initialize every 1000 bars.

 This is a super-efficient version of the Fulks/Simms Linear
 Regression Slope Fast Calc algorithm.  Here, a loop gets executed
 only once during initialization, rather than at every bar.

 This function assumes that the Y-axis (where X=0) always coincides
 with the current bar.  Therefore, the Y-intercept is the same as
 the value of the regression line at the current bar, and is given
 by the formula:

 YIntercept = Average(Price, Length) + slope * Length/2;
}

Inputs:
    Price(NumericSeries),   {values on which to calculate slope}
    Length(NumericSimple),  {lookback length}
    YIntercept(NumericRef); {optional Y-intercept value returned here}

Vars: xLen(0), ix(0), m1(0), m2(0), sumP(0), sumIP(0);

{Re-initialize at first bar, every 1000 bars, or when Length changes}
if xLen <> Length or Mod(CurrentBar, 1000) = 1 then begin
    xLen = Length;
    m1 = 6 / (Length * (Length + 1));
    m2 = 2 / (Length - 1);
    sumP = 0; sumIP = 0;
    for ix = 0 to length-1 begin
        sumP = sumP + Price[ix];
        sumIP = sumIP + ix * Price[ix];
    end;

{Linear regression slope super fast calculation}
end else begin
    sumIP = sumIP + sumP - Length * Price[Length];
    sumP = sumP + Price - Price[Length];
end;

value1 = m1 * (sumP - m2 * sumIP);
YIntercept = sumP/Length + value1 * Length * 0.5;
_LinRegSlopeSFC = value1;