21 citations · 39 across the 12 of their papers we have counts for
8 papers · 1 filter
Multiscale Dynamic Dependence Estimation over Networks
Cristian F. Jiménez-Varón, Marina I. Knight, Matthew A. Nunes
In many settings, observed multivariate time series are often nonstationary in nature, i.e., their second order properties vary over time. An additional feature is that their cross…
Network Estimation for Stationary Time Series
Madeline A. Shelley, Chiara Boetti, Marina I. Knight +1
High-dimensional multivariate time series are common in many scientific and industrial applications, where the interest lies in identifying key dependence structure within the data…
Long memory network time series
Chiara Boetti, Matthew A. Nunes, Marina I. Knight
Many scientific areas, from computer science to the environmental sciences and finance, give rise to multivariate time series which exhibit long memory, or loosely put, a slow deca…
Frequency-Domain Analysis of Time Series with Network-Structured Dependence: Application to Global Bank Connectedness
Cristian F. Jiménez-Varón, Marina I. Knight
Financial spillovers in interconnected systems, such as global banking networks, require tools that capture temporal and frequency dynamics, while incorporating the underlying netw…
A multiscale method for data collected from network edges via the line graph
Dingjia Cao, Marina I. Knight, Guy P. Nason
Data collected over networks can be modelled as noisy observations of an unknown function over the nodes of a graph or network structure, fully described by its nodes and their con…
Automatic Locally Stationary Time Series Forecasting with application to predicting U.K. Gross Value Added Time Series under sudden shocks caused by the COVID pandemic
Rebecca Killick, Marina I. Knight, Guy P. Nason +2
Accurate forecasting of the U.K. gross value added (GVA) is fundamental for measuring the growth of the U.K. economy. A common nonstationarity in GVA data, such as the ABML series,…
Multiscale modelling of replicated nonstationary time series
Jonathan Embleton, Marina I. Knight, Hernando Ombao
Within the neurosciences, to observe variability across time in the dynamics of an underlying brain process is neither new nor unexpected. Wavelets are essential in analyzing brain…
Generalised Network Autoregressive Processes and the GNAR package
Marina Knight, Kathryn Leeming, Guy Nason +1
This article introduces the GNAR package, which fits, predicts, and simulates from a powerful new class of generalised network autoregressive processes. Such processes consist of a…