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05/30/2023
Testing for the Markov Property in Time Series via Deep Conditional Generative Learning
The Markov property is widely imposed in analysis of time series data. C...
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05/22/2023
A two-way heterogeneity model for dynamic networks
Analysis of networks that evolve dynamically requires the joint modellin...
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01/06/2022
Blind Source Separation over Space
We propose a new estimation method for the spatial blind source separati...
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12/31/2021
Modelling matrix time series via a tensor CP-decomposition
We propose to model matrix time series based on a tensor CP-decompositio...
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12/19/2021
Edge differentially private estimation in the β-model via jittering and method of moments
A standing challenge in data privacy is the trade-off between the level ...
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03/17/2021
Simultaneous Decorrelation of Matrix Time Series
We propose a contemporaneous bilinear transformation for matrix time ser...
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01/06/2021
Factor Modelling for Clustering High-dimensional Time Series
We propose a new unsupervised learning method for clustering a large num...
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10/09/2020
Autoregressive Networks
We propose a first-order autoregressive model for dynamic network proces...
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09/03/2020
Probabilistic Forecasting for Daily Electricity Loads and Quantiles for Curve-to-Curve Regression
Probabilistic forecasting of electricity load curves is of fundamental i...
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06/13/2020
A power one test for unit roots based on sample autocovariances
We propose a new unit-root test for a stationary null hypothesis H_0 aga...
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02/02/2020
Modeling Multivariate Spatial-Temporal Data with Latent Low-Dimensional Dynamics
High-dimensional multivariate spatial-temporal data arise frequently in ...
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08/10/2018
On testing for high-dimensional white noise
Testing for white noise is a classical yet important problem in statisti...
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03/07/2018
Estimation of edge density in noisy networks
While it is common practice in applied network analysis to report variou...
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03/05/2018
