Humans are exposed to a diverse mixture of chemical and non-chemical exposures across
their lifetimes. Well-designed epidemiology studies as well as sophisticated exposure …

Over the last two decades, topological data analysis (TDA) has emerged as a very powerful
data analytic approach that can deal with various data modalities of varying complexities …

As improved recording technologies have created new opportunities for neurophysiological
investigation, emphasis has shifted from individual neurons to multiple populations that form …

Gait and balance are an intricate interplay between the brain, nervous system, sensory
organs, and musculoskeletal system. They are greatly influenced by the type of footwear …

Graphical models for nonstationary time series Page 1 The Annals of Statistics 2023, Vol. 51,
No. 4, 1453–1483 https://doi.org/10.1214/22-AOS2205 © Institute of Mathematical Statistics …

State-space models (SSM) with Markov switching offer a powerful framework for detecting
multiple regimes in time series, analyzing mutual dependence and dynamics within regimes …

Many neuroscience experiments record sequential trajectories where each trajectory
consists of oscillations and fluctuations around zero. Such trajectories can be viewed as …

In geostatistical problems with massive sample size, Gaussian processes can be
approximated using sparse directed acyclic graphs to achieve scalable O (n) computational …

The study of the interdependence relationships of the variables of an examined system is of
great importance and remains a challenging task. There are two distinct cases of …

We propose a novel algorithm to extract frequency-band specific and non-linear Granger
causality (Spectral NLGC) connections between components of a multivariate time series …