Related papers: A new development cycle of the Statistical Toolkit
Data scientists and statisticians are often at odds when determining the best approach, machine learning or statistical modeling, to solve an analytics challenge. However, machine learning and statistical modeling are more cousins than…
Comparisons of different treatments or production processes are the goals of a significant fraction of applied research. Unsurprisingly, two-sample problems play a main role in Statistics through natural questions such as `Is the the new…
Collaborative competitions have gained popularity in the scientific and technological fields. These competitions involve defining tasks, selecting evaluation scores, and devising result verification methods. In the standard scenario,…
As the population of world is increasing, and even more concentrated in urban areas, ensuring public safety is becoming a taunting job for security personnel and crowd managers. Mass events like sports, festivals, concerts, political…
Statistics experiences a storm around the perceived misuse and possible abuse of its methods in the context of the so-called reproducibility crisis. The methods and styles of quantification practiced in mathematical modelling rarely make it…
The main goal of this document is to help the research community to understand the basic concepts of software distribution: Free software, Open source software, licenses. This document also includes a procedure for research software and…
Quantum computing has the potential to provide exponential performance benefits in processing over classical computing. It utilizes quantum mechanics phenomena (such as superposition, entanglement, and interference) to solve a computational…
Synthcity is an open-source software package for innovative use cases of synthetic data in ML fairness, privacy and augmentation across diverse tabular data modalities, including static data, regular and irregular time series, data with…
Tick is a statistical learning library for Python~3, with a particular emphasis on time-dependent models, such as point processes, and tools for generalized linear models and survival analysis. The core of the library is an optimization…
sktime is an open source, Python based, sklearn compatible toolkit for time series analysis developed by researchers at the University of East Anglia (UEA), University College London and the Alan Turing Institute. A key initial goal for…
Survival analysis studies time-modeling techniques for an event of interest occurring for a population. Survival analysis found widespread applications in healthcare, engineering, and social sciences. However, the data needed to train…
Power laws are theoretically interesting probability distributions that are also frequently used to describe empirical data. In recent years effective statistical methods for fitting power laws have been developed, but appropriate use of…
The proliferation of open-source scientific software for science and research presents opportunities and challenges. In this paper, we introduce the SciCat dataset -- a comprehensive collection of Free-Libre Open Source Software (FLOSS)…
The SmartSHARK repository mining data is a collection of rich and detailed information about the evolution of software projects. The data is unique in its diversity and contains detailed information about each change, issue tracking data,…
Diffusions are a successful technique to sample from high-dimensional distributions. The target distribution can be either explicitly given or learnt from a collection of samples. They implement a diffusion process whose endpoint is a…
Conventional statistics begins with a model, and assigns a likelihood of obtaining any particular set of data. The opposite approach, beginning with the data and assigning a likelihood to any particular model, is explored here for the case…
Basket trials are a new type of clinical trial in which a treatment is investigated in several subgroups. For the analysis of these trials, information is shared between the subgroups based on the observed data to increase the power. Many…
Over time, software systems suffer gradual quality decay and therefore costs can rise if organizations fail to take proactive countermeasures. Quality control is the first step to avoiding this cost trap. Continuous quality assessments help…
We present a statistical perspective on boosting. Special emphasis is given to estimating potentially complex parametric or nonparametric models, including generalized linear and additive models as well as regression models for survival…
In an era of software crisis, the move of firms towards geographically-distributed software development teams is being challenged by collaboration issues. On this matter, the open-source phenomenon may shed some light, as successful cases…