What does the LookBack feature do?

Best Regards

Rick Osborn

--- On Tue, 4/27/10, brucet30 <bruce...@yahoo.com> wrote:

From: brucet30 <bruce...@yahoo.com>
Subject: [amibroker] Re: linear regression function
To: amibroker@yahoogroups.com
Date: Tuesday, April 27, 2010, 1:27 PM







 



  


    
      
      
      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 );

> 

> 

> 

> 

> --- 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

> > >

> >

>





    
     

    
    


 



  



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