Statistical methods play a significant role throughout the life-cycle of physics experiments, being an essential component of physics analysis. The present project in progress aims to develop an object-oriented software Toolkit for statistical data analysis. The Toolkit contains a variety of Goodness-of-Fit (GoF) tests, from Chi-squared to Kolmogorov-Smirnov, to less known, but generally much more powerful tests such as Anderson-Darling, Goodman, Fisz-Cramer-von Mises, Kuiper. Thanks to the component-based design and the usage of the standard abstract interfaces for data analysis, this tool can be used by other data analysis systems or integrated in experimental software frameworks. In this paper we describe the statistical details of the algorithms and the computational features of the Toolkit. With the aim of showing the consistency between the code and the mathematical features of the algorithms, we describe the results we obtained reproducing by means of the Toolkit a couple of Goodness-of-Fit testing examples of relevance in statistics literature.
Cirrone et al. (Fri,) studied this question.