Abstract: We propose a model to flexibly estimate joint tail properties by exploiting the convergence of an appropriately scaled point cloud onto a compact limit…
Abstract: Remote sensing data sets produced by NASA and other space agencies are a vast resource for the study of climate change and the physical…
Abstract: The human microbiome is the collection of microorganisms that live on and inside of our bodies. Microbiome data are inherently challenging to analyze due…
Abstract: In typical single-cell RNA-seq (scRNA-seq) data analysis, a clustering algorithm is applied to find discrete cell clusters as putative cell types, and then a…
Abstract: Testing a global null is a canonical problem in statistics and has a wide range of applications. In view of the fact of no…
Abstract: We characterize functional brain imaging data, obtained via electroencephalograms, as functional data. Due to the highly observed levels of signal heterogeneity, functional regression analysis…
Abstract: Hidden Markov models are a popular class of time series models where the observation process depends on a latent state process taken to evolve…
Abstract: Epigenetic aging clocks play a pivotal role in estimating an individual's biological age through the examination of DNA methylation patterns at numerous CpG (Cytosine-phosphate-Guanine)…
Abstract: Understanding causal relationships is one of the most important goals of modern science. So far, the causal inference literature has focused almost exclusively on…
Abstract: Recent advances in computing and measurement technologies have led to an explosion in the amount of data with network structures in a variety of…
Abstract: Estimating dynamic treatment effects is essential across various disciplines, offering nuanced insights into the time-dependent causal impact of interventions. However, this estimation presents challenges…
Abstract: Respondent-driven sampling (RDS) is a network-based sampling strategy used to study hidden populations for which no sampling frame is available. In each epoch of…