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Modern bio-technologies have produced a vast amount of high-throughput data with the number of predictors far greater than the sample size. In order to identify more novel biomarkers and understand biological mechanisms, it is vital to…

Machine Learning · Statistics 2018-05-18 Kevin He , Jian Kang , Hyokyoung Grace Hong , Ji Zhu , Yanming Li , Huazhen Lin , Han Xu , Yi Li

Is there a natural way to order data in dimension greater than one? The approach based on the notion of data depth, often associated with John Tukey, is among the most popular. Tukey's depth has found applications in robust statistics,…

Statistics Theory · Mathematics 2026-01-13 Stanislav Minsker , Yinan Shen

The discovery of disease subtypes is an essential step for developing precision medicine, and disease subtyping via omics data has become a popular approach. While promising, subtypes obtained from conventional approaches may not be…

Applications · Statistics 2023-09-28 Lingsong Meng , Zhiguang Huo

Kernel density estimation on a finite interval poses an outstanding challenge because of the well-recognized bias at the boundaries of the interval. Motivated by an application in cancer research, we consider a boundary constraint linking…

Statistics Theory · Mathematics 2020-12-01 Matthew J. Colbrook , Zdravko I. Botev , Karsten Kuritz , Shev MacNamara

Stress testing poses a causal question: how would portfolio credit losses change if the macroeconomy followed an adverse counterfactual path? Yet standard practice remains predictive and might be therefore vulnerable to omitted-variable…

Artificial Intelligence · Computer Science 2026-05-19 Yu Wang , Xiangchen Liu , Siguang Li

Bartholomew's trend test belongs to the broad class of isotonic regression models, specifically with a single qualitative factor, e.g. dose levels. Using the approximation of the ANOVA F-test by the maximum contrast test against grand mean…

Methodology · Statistics 2024-01-25 Ludwig A. Hothorn

This paper presents a Bayesian approach to multiple-output quantile regression. The unconditional model is proven to be consistent and asymptotically correct frequentist confidence intervals can be obtained. The prior for the unconditional…

Methodology · Statistics 2022-05-11 Michael Guggisberg

Gaussian Process Regression (GPR) is a Bayesian method for inferring profiles based on input data. The technique is increasing in popularity in the fusion community due to its many advantages over traditional fitting techniques including…

Methodology · Statistics 2022-09-07 Jarrod Leddy , Sandeep Madireddy , Eric Howell , Scott Kruger

When performing a time series analysis of continuous data, for example from climate or environmental problems, the assumption that the process is Gaussian is often violated. Therefore, we introduce two non-Gaussian autoregressive time…

Methodology · Statistics 2021-03-02 Yuan Yan , Marc Genton

A transversal topic of my research has been the development and application of computational methods for DNA sequence analysis. The methods I have been developing aim at improving our understanding of the regulation processes happening in…

Genomics · Quantitative Biology 2014-09-24 Valentina Boeva

We introduce a multiple testing procedure (TreeBH) which addresses the challenge of controlling error rates at multiple levels of resolution. Conceptually, we frame this problem as the selection of hypotheses which are organized…

Methodology · Statistics 2018-10-25 Marina Bogomolov , Christine B. Peterson , Yoav Benjamini , Chiara Sabatti

We propose an adjusted likelihood ratio test of two-factor separability (Kronecker product structure) for unbalanced multivariate repeated measures data. Here we address the particular case where the within subject correlation is believed…

Methodology · Statistics 2011-02-02 Sean L. Simpson

The Model-X knockoff procedure has recently emerged as a powerful approach for feature selection with statistical guarantees. The advantage of knockoff is that if we have a good model of the features X, then we can identify salient features…

Machine Learning · Statistics 2019-05-30 Jaime Roquero Gimenez , James Zou

For a genomically unstable cancer, a single tumour biopsy will often contain a mixture of competing tumour clones. These tumour clones frequently differ with respect to their genomic content (copy number of each gene) and structure (order…

Genomics · Quantitative Biology 2015-04-28 Andrew McPherson , Andrew Roth , Gavin Ha , Sohrab P. Shah , Cedric Chauve , S. Cenk Sahinalp

With the advent of so-called default Bayesian hypothesis tests, scientists in applied fields have gained access to a powerful and principled method for testing hypotheses. However, such default tests usually come with a compromise,…

Computation · Statistics 2021-12-07 Thomas J. Faulkenberry

Most conventional risk analysis methods rely on a single best estimate of exposure per person which does not allow for adjustment for exposure-related uncertainty. Here, we propose a Bayesian model averaging method to properly quantify the…

Applications · Statistics 2020-04-07 Deukwoo Kwon , F. Owen Hoffman , Brian E. Moroz , Steven L. Simon

Phenotype variations define heterogeneity of biological and molecular systems, which play a crucial role in several mechanisms. Heterogeneity has been demonstrated in tumor cells. Here, samples from blood of patients affected from colon…

Biological Physics · Physics 2015-11-09 Giuseppina Simone

The concept of statistical depth extends the notions of the median and quantiles to other statistical models. These procedures aim to formalize the idea of identifying deeply embedded fits to a model that are less influenced by…

Statistics Theory · Mathematics 2026-05-11 Jorge G. Adrover , Marcelo Ruiz

Externally controlled trials (ECTs) are increasingly used when randomized controls are infeasible, unethical, or insufficient, including applications in rare diseases, oncology, pediatrics, and post-approval effectiveness research. Although…

There are numerous stochastic models for cancer risk for a given tissue. Many rely on the following two hypotheses. 1. There is a fixed probability that a given cell division will eventually lead to a cancerous cell. 2. Cell divisions are…

Tissues and Organs · Quantitative Biology 2015-08-20 Rinaldo B. Schinazi
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