April 12, 2007 Robust statistical analysis methods capable of dealing with large complex data sets are required more than ever before in almost all branches of science. The European Science Foundation ...

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 ...

Robust estimation and outlier detection play a critical role in modern data analysis, particularly when dealing with high-dimensional datasets. In such contexts, classical statistical methods often ...

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 ...

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 ...

Kaitlyn Cook is a biostatistician working to develop robust statistical methods for infectious disease treatment and prevention trials. Her research draws on ideas from the missing data literature, ...

Chongzhi Di develops statistical methods for analyzing functional and longitudinal data in epidemiologic studies of physical activity and sedentary behavior, particularly using data from mobile-health ...