24 citations · 50 across the 49 of their papers we have counts for
34 papers · 1 filter
Partial Wavelet Canonical Coherence for Nonstationary Signals with High Dimensional Confounders
Haibo Wu, Marina I. Knight, Hernando Ombao
We develop Partial Wavelet Canonical Coherence for measuring the direct canonical association between two multivariate nonstationary time series after adjustment for possibly high-…
Topological Effective Connectivity Modeling in Brain Networks
Anass El-Yaagoubi, Moo K. Chung, Hernando Ombao
Characterizing directed information flow in brain networks is difficult because neural circuits are full of recurrent feedback loops. Many existing tools for directed dependence as…
Forecasting Multivariate Time Series under Predictive Heterogeneity: A Validation-Driven Clustering Framework
Ziling Ma, Ángel López Oriona, Hernando Ombao +1
We study adaptive pooling under predictive heterogeneity in high-dimensional multivariate time series forecasting, where global models improve statistical efficiency but may fail t…
Filtration-Based Learning of Multiscale Shared Structures for Multiple Functional Predictors
Shuhao Jiao, Hernando Ombao, Ian W. McKeague
It is crucial to learn the shared structures among functional predictors, as these structures characterize how predictor components exert common effects and, more generally, how pr…
FCPCA: Fuzzy clustering of high-dimensional time series based on common principal component analysis
Ziling Ma, Ángel López-Oriona, Hernando Ombao +1
Clustering multivariate time series data is a crucial task in many domains, as it enables the identification of meaningful patterns and groups in time-evolving data. Traditional ap…
Wavelet Canonical Coherence for Nonstationary Signals
Haibo Wu, Marina I. Knight, Keiland W. Cooper +2
Understanding the evolving dependence between two clusters of multivariate signals is fundamental in neuroscience and other domains where sub-networks in a system interact dynamica…