Er - Ah nothing.
I created this from a more complicated piece of code that calculated a fit to a
quadratic equation, and had several additional features that I removed.
Reef
--- In amibroker@yahoogroups.com, ri...@... wrote:
>
> What does the LookBack feature do?
>
> Best Regards
>
> Rick Osborn
>
> --- On Tue, 4/27/10, brucet30 <bruce...@...> wrote:
>
> From: brucet30 <bruce...@...>
> Subject: [amibroker] Re: linear regression function
> To: amibroker@yahoogroups.com
> Date: Tuesday, April 27, 2010, 1:27 PM
>
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> Â
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>
> Thanks, this is what I was looking for.
>
>
>
> --- In amibro...@yahoogrou ps.com, "reefbreak_sd" <reefbreak_sd@ ...> wrote:
>
> >
>
> > This is a Linear Reg fit using the equations from "Standard Math Tables"
> > published by CRC. The Y axis uses the array 'Prc', the X axis uses the
> > array 'X'. You can put any values you want into those two arrays.
>
> >
>
> > To get it to work you need to 'Insert' it into a Chart Window
>
> > then click on the last bar.
>
> > The answers come out in the Interpretation window.
>
> > This was coded for comfort - not for speed.
>
> > Watch out for line wraps
>
> >
>
> >
>
> > //Linear Regression Fit with Standard Error function;
>
> > // Ed Hoopes
>
> > // April 2008
>
> > // Rev A - Started with QFit
>
> >
>
> >
>
> > // ************ ********* ********* * Linear Regression Fit
> > ************ ********* *******;
>
> >
>
> > Pers = Param("Periods" , 20, 5, 200, 1 );
>
> > LookBack = Param("Look Back", 0, 0, 500, 1 );
>
> >
>
> > SetBarsRequired( 100 );
>
> >
>
> > //Prc = (Open + High + Low + Close ) / 4 ;
>
> > Prc = Close;
>
> >
>
> > //Initialize variables;
>
> > SUMX = 0.00; SUMY = 0.00;
>
> > SUMXY = 0.00; SUMX2 = 0.00;
>
> > // X[0] = 0.00;
>
> >
>
> > for (i = 0; i < BarCount; i++ )
>
> > {
>
> > X[i] = 0;
>
> > }
>
> >
>
> > for (j = BarCount - 1 - Pers; j < BarCount; j++ )
>
> > {
>
> > X[j] = X[j-1] + 1;
>
> > }
>
> >
>
> > //Calculate SUMS;
>
> >
>
> > SumX = Sum(X, Pers );
>
> > SumY = Sum(Prc, Pers );
>
> > SumX2 = Sum(X*X, Pers );
>
> > SumXY = Sum(X*Prc, Pers );
>
> >
>
> >
>
> > // Calculate the Slope;
>
> > SlopeNumerator = Pers * SumXY - SumX * SumY ;
>
> > SlopeDenominator = Pers * SumX2 - SumX * SumX ;
>
> > Slope = SlopeNumerator / SlopeDenominator ;
>
> >
>
> > // Calculate the Intercept;
>
> > InterceptTerm1 = SumY / Pers ;
>
> > InterceptTerm2 = Slope * SumX / Pers;
>
> > Intercept = InterceptTerm1 - InterceptTerm2;
>
> >
>
> > // Calculate the Standard Error;
>
> >
>
> > SumSE = Sum((Prc - (intercept + Slope * X))^2, Pers );
>
> > DenomSE = Pers - 2;
>
> > StErr = sqrt(SumSE / DenomSE );
>
> >
>
> > printf("Slope = " + Slope + "\n" );
>
> > printf("Intercept = " + Intercept + "\n" );
>
> > printf("StdErr = " + StErr + "\n" );
>
> >
>
> > Plot(Slope, "Prc", colorYellow, styleLine + styleThick );
>
> >
>
> >
>
> >
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> >
>
> > --- In amibro...@yahoogrou ps.com, "Mike" <sfclimbers@ > wrote:
>
> > >
>
> > > I haven't looked into either myself, but the two most common answers to
> > > alternative array manipulations are:
>
> > >
>
> > > Osaka DLL http://www.amibroke r.org/3rdparty/
>
> > > R Plugin http://www.amibroke r.com/members/
>
> > >
>
> > > Of course, you could always just write your own function:
>
> > >
>
> > > http://www.amibroke r.com/guide/ a_userfunctions. html
>
> > >
>
> > > Mike
>
> > >
>
> > > --- In amibro...@yahoogrou ps.com, "brucet30" <brucet30@> wrote:
>
> > > >
>
> > > > I am looking for some AFL code that would perform a linear regression
> > > > on two arrays (x, y) and return the intercept and slope for this data
> > > > set. THe only funcitons I have been able to find so far in the AFL
> > > > library and elsewhere assume the x-axis is time and the y-axis is price
> > > > of some other indicator series. I need something more general, that
> > > > could work with any (X,y) data set. Any help on this would be very much
> > > > appreciated.
>
> > > > Thanks
>
> > > >
>
> > >
>
> >
>
