The Linear Template Fit is a matrix formalism for the determination of the best estimator for simulation-based parameter estimation. The Linear Template Fit combines a linear regression with a linear least-squares method and its optimization. All predictions need to be calculated beforehand and those are provided for a few selected values for the parameter(s) of interest. The Linear Template Fit may be useful for a wide variety of fitting problems. More details are provided in Eur.Phys.J.C 82 (2022) 731 arXiv:2112.01548.
The Linear Template Fit is provided as two (almost) independent implementations, where the difference is in the linear algebra package that is used for the calculations
LTF_Eigen
makes use of the Eigen linear algebra packageLTF_ROOT
makes use of ROOT's linear algebra package
Both implementations require a C++17 compatible C++ compiler.
Both implementations provide a set of example programs.
The Eigen-based implementation is located in the directory LTF_Eigen
.
Note that the Eigen-based implementation can be used without ROOT
. However, for additional functionality, like the generation of plots, this branch can optionally be linked also with ROOT.
The ROOT-based implementation is located in the directory LTF_ROOT
.
The ROOT-based implemenatatoin requires ROOT version 6 (6.26 is recommended) and further requires the tool CMake3
for compilation.
The ROOT implementation was provided by E. Offermann.
The pre-print is available from arXiv: arXiv:2112.01548
The code repository is hosted at: github.com/britzger/LinearTemplateFit
A Doxygen documentation is at: www.mpp.mpg.de/~britzger/LinearTemplateFit/doxygen
Some lmited further documentation is available from: www.mpp.mpg.de/~britzger/LinearTemplateFit
On a machine with CentOS7 and cvmfs
, one can source lcgenv-LCG_97-x86_64-centos7-gcc9-opt.sh
to get a recent C++ compiler and ROOT.