https://www.tcspc.com/ 2026-04-23T01:18:25+00:00 https://www.tcspc.com/ https://www.tcspc.com/lib/exe/fetch.php/logo.png text/html 2015-02-10T16:34:33+00:00 Anonymous (anonymous@undisclosed.example.com) https://www.tcspc.com/doku.php/glossary:marquardt-levenberg?rev=1423586073&do=diff <table><tr><th colspan="2" width="50%">2014/01/21 16:37</th><th colspan="2" width="50%">current</th></tr><tr><td class="diff-blockheader" colspan="2">Line 1:</td> <td class="diff-blockheader" colspan="2">Line 1:</td> </tr> <tr><td class="diff-lineheader">&#160;</td><td class="diff-context">====== Marquardt-Levenberg ======</td><td class="diff-lineheader">&#160;</td><td class="diff-context">====== Marquardt-Levenberg ======</td></tr> <tr><td class="diff-lineheader">&#160;</td><td class="diff-context"></td><td class="diff-lineheader">&#160;</td><td class="diff-context"></td></tr> <tr><td class="diff-lineheader">-</td><td class="diff-deletedline">The Marquardt-Levenberg method is a means of optimising parameters in a least squares fit. It is used in our [[FluoFit]], [[SymPhoTime]] and a variety of other products (online-Fitting, FluoLib...).</td><td class="diff-lineheader">+</td><td class="diff-addedline">The Marquardt-Levenberg method is a means of optimising parameters in a least squares fit. It is used in our [[<strong class="diff-mark">software:</strong>FluoFit]], [[<strong class="diff-mark">software:</strong>SymPhoTime]] and a variety of other products (online-Fitting, FluoLib...).</td></tr> <tr><td class="diff-lineheader">&#160;</td><td class="diff-context"></td><td class="diff-lineheader">&#160;</td><td class="diff-context"></td></tr> <tr><td class="diff-lineheader">&#160;</td><td class="diff-context">Basically it works by examining how changes of a certain parameter affect the residuals trace, that means, it calculates a pointwise gradient of the residuals trace for each parameter. Marquard-Levenberg optimisation is fairly efficient and is regarded as state-of-the-art in least squares fitting.</td><td class="diff-lineheader">&#160;</td><td class="diff-context">Basically it works by examining how changes of a certain parameter affect the residuals trace, that means, it calculates a pointwise gradient of the residuals trace for each parameter. Marquard-Levenberg optimisation is fairly efficient and is regarded as state-of-the-art in least squares fitting.</td></tr> </table>