30 papers
Adaptive Multi-Scale Forecasting and Gate-Localized Conformal Prediction for Multivariate Nonstationary Time Series
Ziling Ma, Junshu Jiang, Ãngel López-Oriona +2
We propose ABF-T-GLCP, a model-agnostic framework for forecasting and uncertainty quantification in nonstationary multivariate time series. The central idea is to learn an adaptive…
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-…
Dynamic cross-scale wavelet coherence
Haibo Wu, Marina I. Knight, Hernando Ombao
This paper develops a novel statistical approach that allows for the {\em first time} the {\em cross}-oscillatory characterisation of temporally localised interactions between chan…
Spectral Topological Data Analysis of Brain Signals
Anass El-Yaagoubi, Shuhao Jiao, Moo K. Chung +1
Topological analyses of brain functional connectivity usually reduce each pair of channels to a single scalar dependence, typically the Pearson correlation, and so cannot resolve t…
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…
Vector Space of Cycles
Moo K. Chung, Anass B. El-Yaagoubi, Hernando Ombao
Most statistical and machine learning methods for directed interactions focus on pairwise effects among variables. Even existing cyclic models represent feedback primarily through…