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## RE: regress vs polyfit

**From**: |
Allen.Windhorn |

**Subject**: |
RE: regress vs polyfit |

**Date**: |
Mon, 20 Jun 2011 09:31:03 -0500 |

Thomas,
-----Original Message-----
From: address@hidden
[mailto:address@hidden On Behalf Of Thomas Grzybowski
>* I am new to octave and want to fit a single regression line to*
>* some data. I have been using polyfit, and was looking at*
>* regress, but I find regress confusing. From the regress*
>* "Help":*
>
>* * `X' is a matrix of regressors, with the first column filled*
>* with the constant value 1*
>
>* I do not understand the help instructions. My data is simply*
>* x,y pairs - what is this help about - "the constant value 1" ?*
I haven't used regress before -- thanks for bringing it to my
attention. It looks as if it is a more general least-squares
algorithm. For linear fitting you would just make your X matrix
something like:
X =
1.000000 0.103900
1.000000 0.092700
1.000000 0.082700
1.000000 0.073900
1.000000 0.065900
1.000000 0.058700
1.000000 0.052400
1.000000 0.046900
1.000000 0.041800
1.000000 0.037300
where the second column is the "real" x values. The program
appears to fit an equation like y = a0*x0+a1*x1+a2*x2... where
a0 is the constant term and the x0's are all 1, so that if you
didn't want a constant term you would just omit that first
column. Of course if you were fitting more than one variable
you would add columns of x's to the X matrix, and if you were
doing a polynomial fit the first column would be 1, the next
x, then x^2, then x^3 etc.
Regards,
Allen