Cluster-robust inference and estimation methods have emerged as indispensable tools in empirical research, enabling statisticians and economists to draw valid conclusions from data exhibiting ...

The newly developed Huber mean provides a more stable and reliable way to compute averages for data lying on curved geometric spaces, or Riemannian manifolds. By combining the strengths of ...

Dr Max Welz introduces research aiming to make statistical analyses robust against so-called ‘contamination’ in rating data stemming from low-quality survey responses. Empirical research in the social ...

Professor Klaus Nordhausen develops modern multivariate statistical methods to analyze high-dimensional and large datasets in different fields.

A new robust statistical method resists outliers, improving data reliability in AI, robotics, and medical imaging BUSAN, South Korea, Nov. 13, 2025 /PRNewswire/ -- In many modern sciences, data often ...

In the pharmaceutical industries, validation of analytical methods is a critical process that confirms the reliability and appropriateness of a method for its intended application. Method validation ...

Faculty in the Statistical Learning and Data Science Hub advance statistical and machine learning methods tailored to the unique challenges of biomedical and epidemiologic data, including ...

A recent study by Kompetenzzentrum Wasser Berlin addresses a critical challenge in agricultural water reuse: how to validate that water treatment plants are able to meet regulatory performance targets ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...