<div dir="ltr">Hello Stéphane,<div><br></div><div>thank you! I solved the problem with your hint. For further reference I attach a ZIP file with a linear regression comparing statistical results from Scilab and gnuplot.</div><div><br></div><div>Regards</div><div><br></div><div>Pablo</div><div><br></div><div><br></div></div><div class="gmail_extra"><br><div class="gmail_quote">2015-09-17 11:43 GMT-03:00 Stéphane Mottelet <span dir="ltr"><<a href="mailto:stephane.mottelet@utc.fr" target="_blank">stephane.mottelet@utc.fr</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div bgcolor="#FFFFFF" text="#000000">
<div>Hello,<br>
<br>
You can use the numderivative macro, with your residual function
as first argument.<br>
<br>
hth<br>
<br>
S.<div><div class="h5"><br>
<br>
<br>
Le 17/09/2015 16:18, Pablo Caron a écrit :<br>
</div></div></div>
<blockquote type="cite"><div><div class="h5">
<div dir="ltr">
<div class="gmail_quote">
<div dir="ltr">Dear user group,
<div><br>
</div>
<div>I need to extract the Jacobian from the lsqrsolve
function. The fortran routine lmdif (<a href="http://www.netlib.org/minpack/lmdif.f" target="_blank"></a><a href="http://www.netlib.org/minpack/lmdif.f" target="_blank">http://www.netlib.org/minpack/lmdif.f</a>)
provide this as the output fjac, but lsqrsolve does not
have this option.</div>
<div><br>
</div>
<div>I need to evaluate the goodness of a regression I made
using lsqrsolve and I found that this is done through the
correlation matrix. I need either the correlation matrix
or the jacobian.<br>
</div>
<div><br>
</div>
<div>I would like to get an output similar to the following
<div><font face="monospace, monospace"><br>
</font></div>
<div><font face="monospace, monospace">Final set of
parameters Asymptotic Standard Error</font></div>
<div><font face="monospace, monospace">=======================
==========================</font></div>
<div><font face="monospace, monospace">m = 0.174844 Â Â Â
   +/- 0.0002964 (0.1695%)</font></div>
<div><font face="monospace, monospace">b = 1506.34 Â Â Â Â
  +/- 5.756 (0.3821%)</font></div>
<div><font face="monospace, monospace"><br>
</font></div>
<div><font face="monospace, monospace">correlation matrix
of the fit parameters:</font></div>
<div><font face="monospace, monospace">    m   b</font></div>
<div><font face="monospace, monospace">m  1.000</font></div>
<div><font face="monospace, monospace">b -0.448 1.000</font></div>
</div>
<div><font face="monospace, monospace"><br>
</font></div>
Regards<span><font color="#888888"><br>
<br>
Pablo</font></span></div>
</div>
<br>
</div>
<br>
<fieldset></fieldset>
<br>
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<pre cols="72">--
Département de Génie Informatique
EA 4297 Transformations Intégrées de la Matière Renouvelable
Université de Technologie de Compiègne - CS 60319
60203 Compiègne cedex</pre>
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