Efficient maximum likelihood estimator fitting of histograms

Access through your institution Buy or subscribe To the Editor: Scientists commonly form histograms of counted events from their data, and extract parameters by fitting to a known model.

Anytime a scientist counts photons, molecules, cells or data for individuals in histogram bins and fits that to a distribution, he or she is fitting an event-counting histogram. Here we aim

to convince the scientific community to use the maximum likelihood estimator (MLE) for Poisson deviates when fitting event-counting histograms rather than the typically used least-squares

measure. We describe how to use the MLE to fit data efficiently and robustly, and provide example code (Supplementary Software). This is a preview of subscription content, access via your

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Download references ACKNOWLEDGEMENTS This work was performed under the auspices of the US Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344.

AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California, USA Ted A Laurence & Brett A Chromy

Authors * Ted A Laurence View author publications You can also search for this author inPubMed Google Scholar * Brett A Chromy View author publications You can also search for this author

inPubMed Google Scholar CORRESPONDING AUTHOR Correspondence to Ted A Laurence. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing financial interests. SUPPLEMENTARY

INFORMATION SUPPLEMENTARY TEXT AND FIGURES Supplementary Note (PDF 870 kb) SUPPLEMENTARY SOFTWARE C code for Levenberg-Marquardt minimization of MLE. (ZIP 17 kb) RIGHTS AND PERMISSIONS

Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Laurence, T., Chromy, B. Efficient maximum likelihood estimator fitting of histograms. _Nat Methods_ 7, 338–339 (2010).

https://doi.org/10.1038/nmeth0510-338 Download citation * Issue Date: May 2010 * DOI: https://doi.org/10.1038/nmeth0510-338 SHARE THIS ARTICLE Anyone you share the following link with will

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