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<title>GNU Scientific Library &ndash; Reference Manual: Least-Squares Fitting</title>

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<a name="Least_002dSquares-Fitting"></a>
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<p>
Next: <a href="Nonlinear-Least_002dSquares-Fitting.html#Nonlinear-Least_002dSquares-Fitting" accesskey="n" rel="next">Nonlinear Least-Squares Fitting</a>, Previous: <a href="Multidimensional-Minimization.html#Multidimensional-Minimization" accesskey="p" rel="previous">Multidimensional Minimization</a>, Up: <a href="index.html#Top" accesskey="u" rel="up">Top</a> &nbsp; [<a href="Function-Index.html#Function-Index" title="Index" rel="index">Index</a>]</p>
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<hr>
<a name="Least_002dSquares-Fitting-1"></a>
<h2 class="chapter">38 Least-Squares Fitting</h2>
<a name="index-fitting"></a>
<a name="index-least-squares-fit"></a>
<a name="index-regression_002c-least-squares"></a>
<a name="index-weighted-linear-fits"></a>
<a name="index-unweighted-linear-fits"></a>
<p>This chapter describes routines for performing least squares fits to
experimental data using linear combinations of functions.  The data
may be weighted or unweighted, i.e. with known or unknown errors.  For
weighted data the functions compute the best fit parameters and their
associated covariance matrix.  For unweighted data the covariance
matrix is estimated from the scatter of the points, giving a
variance-covariance matrix.
</p>
<p>The functions are divided into separate versions for simple one- or
two-parameter regression and multiple-parameter fits.
</p>
<table class="menu" border="0" cellspacing="0">
<tr><td align="left" valign="top">&bull; <a href="Fitting-Overview.html#Fitting-Overview" accesskey="1">Fitting Overview</a>:</td><td>&nbsp;&nbsp;</td><td align="left" valign="top">
</td></tr>
<tr><td align="left" valign="top">&bull; <a href="Linear-regression.html#Linear-regression" accesskey="2">Linear regression</a>:</td><td>&nbsp;&nbsp;</td><td align="left" valign="top">
</td></tr>
<tr><td align="left" valign="top">&bull; <a href="Multi_002dparameter-regression.html#Multi_002dparameter-regression" accesskey="3">Multi-parameter regression</a>:</td><td>&nbsp;&nbsp;</td><td align="left" valign="top">
</td></tr>
<tr><td align="left" valign="top">&bull; <a href="Regularized-regression.html#Regularized-regression" accesskey="4">Regularized regression</a>:</td><td>&nbsp;&nbsp;</td><td align="left" valign="top">
</td></tr>
<tr><td align="left" valign="top">&bull; <a href="Robust-linear-regression.html#Robust-linear-regression" accesskey="5">Robust linear regression</a>:</td><td>&nbsp;&nbsp;</td><td align="left" valign="top">
</td></tr>
<tr><td align="left" valign="top">&bull; <a href="Large-Dense-Linear-Systems.html#Large-Dense-Linear-Systems" accesskey="6">Large Dense Linear Systems</a>:</td><td>&nbsp;&nbsp;</td><td align="left" valign="top">
</td></tr>
<tr><td align="left" valign="top">&bull; <a href="Troubleshooting.html#Troubleshooting" accesskey="7">Troubleshooting</a>:</td><td>&nbsp;&nbsp;</td><td align="left" valign="top">
</td></tr>
<tr><td align="left" valign="top">&bull; <a href="Fitting-Examples.html#Fitting-Examples" accesskey="8">Fitting Examples</a>:</td><td>&nbsp;&nbsp;</td><td align="left" valign="top">
</td></tr>
<tr><td align="left" valign="top">&bull; <a href="Fitting-References-and-Further-Reading.html#Fitting-References-and-Further-Reading" accesskey="9">Fitting References and Further Reading</a>:</td><td>&nbsp;&nbsp;</td><td align="left" valign="top">
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