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Statistics::Basic::LeastSquareFit.3pm

NAME

Statistics::Basic::LeastSquareFit - find the least square fit for two arrays

SYNOPSIS

A machine to calculate the Least Square Fit of given vectors x and y.

The module returns the alpha and beta that best fits this formula:

     $y = $beta * $x + $alpha
 
 

Invoke it this way:

     my $lsf = leastsquarefit( [1,2,3], [1,2,3] );
 
 

Or this way:

     my $v1  = vector(1,2,3);
     my $v2  = vector(1,2,3);
     my $lsf = lsf($v1,$v2);
 
 

And then either query the values or print them like so:

     print "The LSF for $v1 and $v2: $lsf\n";
     my ($alpha, $beta) = $lsf->query;
 
 

LSF is meant for finding a line of best fit. $beta is the slope of the line and $alpha is the y-offset. Suppose you want to draw the line. Use these to calculate the "x" for a given "y" or vice versa:

     my $y = $lsf->y_given_x( 7 );
     my $x = $lsf->x_given_y( 7 );
 
 

(Note that "x_given_y()" can sometimes produce a divide-by-zero error since it has to divide by the $beta.)

Create a 20 point ``moving'' LSF like so:

     my $sth = $dbh->prepare("select col1,col2 from data where something");
     my $len = 20;
     my $lsf = lsf();
        $lsf->set_size($len);
 
     $sth->execute or die $dbh->errstr;
     $sth->bind_columns( my ($lhs, $rhs) ) or die $dbh->errstr;
 
     my $count = $len;
     while( $sth->fetch ) {
 
         $lsf->insert( $lhs, $rhs );
         if( -- $count <= 0 ) {
             print "LSF: $lsf\n";
         }
     }
 
 

The full details are probably in the base module. If you have questions, just let me know.

AUTHOR

Paul Miller "<jettero@cpan.org>"

COPYRIGHT

Copyright 2009 Paul Miller --- Licensed under the LGPL

SEE ALSO

perl(1), Statistics::Basic