myFitter is hosted by Hepforge, IPPP Durham

myFitter - Maximum Likelihood Fits in C++ and Python

myFitter is a library for maximum likelihood fits and the numerical computation of p-values in likelihood ratio tests. It has been implemented independently in C++ and Python.

In some situations the statistical significance (p-value) of a likelihood ratio test can not be computed analytically. This is, for example, the case when some parameters of the model are only allowed to float within a certain range or when the models being compared are not nested, meaning that neither model can be obtained from the other by fixing some of its parameters.

myFitter implements a method for efficient numerical computation of p-values. This method is also applicable in the case of non-nested models. It also provides a convenient framework for performing combined fits of data from different experiments.

Citation Guide

The algorithms implemented in myFitter are discussed in

M. Wiebusch, "Numerical Computation of p-values with myFitter," Comput. Phys. Commun. (2013), DOI: 10.1016/j.cpc.2013.06.008, [arXiv:1207.1446v2]

If you use myFitter for a scientific publication, please cite this article. In addition, please follow the citation guidelines of the Dvegas package, which myFitter links to.

C++ Versions

Python Versions

Additional material

The python version is still at an early stage of development and currently lacks complete documentation. A basic and fairly pedagogical introduction was given in a software tutorial at the YETI school 2014 in Durham. The material for the tutorial can be found here.


Please send bugreports to Martin Wiebusch