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 ...
Divergence estimators have emerged as quintessential tools in statistical inference, particularly in contexts where traditional likelihoodâbased methods fail under model misspecification or data ...
Faculty develop methods for structured and unstructured biomedical data that advance statistical inference, machine learning, causal inference, and algorithmic modeling. Their work delivers principled ...
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, ...
Faculty in the Statistics in Epidemiology Hub develop statistical methods to guide population-level research on cancer prevention, early detection, and real-world outcomes. Their work supports the ...
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