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.TH reglin 1 "April 1993" "Scilab Group" "Scilab Function"
.so ../sci.an
.SH NAME
reglin - Linear regression
.SH CALLING SEQUENCE
.nf
[a,b,sig]=reglin(x,y)
.fi
.SH DESCRIPTION
solve the regression problem y=a*x+ b in the least square sense.
\fRsig\fV is the standard deviation of the residual. \fVx\fR and \fVy\fR
are two matrices of size \fRx(p,n)\fV and \fRy(q,n)\fV, so the estimator
\fRa\fV is a matrix
of size \fV(q,p)\fR and \fRb\fV is a vector of size \fR(q,1)\fV
.SH EXAMPLE
.nf
// simulation of data for a(3,5) and b(3,1)
x=rand(5,100);
aa=matrix('magi',5);aa=aa(1:3,:);
bb=[9;10;11]
y=aa*x +bb*ones(1,100)+ 0.1*rand(3,100);
// identification
[a,b,sig]=reglin(x,y);
maxi(abs(aa-a))
maxi(abs(bb-b))
// an other example : fitting a polynom
f=1:100; x=[f.*f; f];
y= [ 2,3]*x+ 10*ones(f) + 0.1*rand(f);
[a,b]=reglin(x,y)
.fi
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