Found 29 papers
Sorted by: Newest FirstMixture Modeling for Temporal Point Processes with Memory
Bruno Sansó, Xiaotian Zheng, Athanasios Kottas
A Physics-Informed Spatiotemporal Deep Learning Framework for Turbulent Systems
Luca Menicali, Andrew Grace, David H. Richter et al.
Autoregressive networks with dependent edges
Qiwei Yao, Jinyuan Chang, Qin Fang et al.
Abstract We propose an autoregressive framework for modelling dynamic networks with dependent edges. It encompasses models that acco...
Tail-robust factor modelling of vector and tensor time series in high dimensions
Haeran Cho, Matteo Barigozzi, Hyeyoung Maeng
Summary We study the problem of factor modelling vector- and tensor-valued time series in the presence of heavy tails in the data, w...
Testing for integer integration in functional time series
Won-Ki Seo, Han Lin Shang
Generalized Multivariate Threshold Autoregressive Models with Linearly Partitioned Threshold Space
Gan Yuan, Chun Yip Yau
Beyond the mean: limit theory and tests for infinite-mean autoregressive conditional durations
Giuseppe Cavaliere, Thomas Mikosch, Anders Rahbek et al.
Abstract Integrated autoregressive conditional duration (ACD) models serve as counterparts to integrated generalized autoregressive ...
Structural Identification for Spatio-Temporal Dynamic Models
Cong Cheng, Yuan Ke, Wenyang Zhang et al.
Localized Sparse Principal Component Analysis of Multivariate Time Series in the Frequency Domain
Amita Manatunga, Jamshid Namdari, Fabio Ferrarelli et al.
Stationarity of Manifold Time Series
Dehan Kong, Junhao Zhu, Zhaolei Zhang et al.
A Statistician’s Overview of Physics-Informed Neural Networks for Spatio-Temporal Data
Christopher K. Wikle, Joshua North, Giri Gopalan et al.
A factor-copula latent-vine time series model for extreme flood insurance losses
Xiaoting Li, Harry Joe, Christian Genest
Efficient Online Prediction for High-Dimensional Time Series via Joint Tensor Tucker Decomposition
Defeng Sun, Zhenting Luan, Haoning Wang et al.
Real-time prediction plays a vital role in various control systems, such as traffic congestion control and wireless channel resource allocation. In th...
Identification and estimation for matrix time series CP-factor models
Qiwei Yao, Jinyuan Chang, Yue Du et al.
Spatiotemporal Besov Priors for Bayesian Inverse Problems
Shiwei Lan, Mirjeta Pasha, Shuyi Li et al.
Spectral change point estimation for high-dimensional time series by sparse tensor decompositionGet access
Xinyu ZhangandKung-Sik Chan
Estimation of Grouped Time-Varying Network Vector Autoregressive Models
Degui Li, Bin Peng, Songqiao Tang et al.
On Non-asymptotic Theory of Recurrent Neural Networks in Temporal Point Processes
Zhiheng Chen, Guanhua Fang, Wen Yu
Temporal point process (TPP) is an important tool for modeling and predicting irregularly timed events across various domains. Recently, the recurrent...
Dynamic Bayesian Learning for Spatiotemporal Mechanistic Models
Sudipto Banerjee, Xiang Chen, Ian Frankenburg et al.
We develop an approach for Bayesian learning of spatiotemporal dynamical mechanistic models. Such learning consists of statistical emulation of the me...
Simultaneous inference for monotone and smoothly time-varying functions under complex temporal dynamics
Tianpai Luo, Weichi Wu
Optimal Vintage Factor Analysis with Deflation Varimax
Xin Bing, Xin He, Dian Jin et al.
Identifying the Structure of High-Dimensional Time Series via Eigen-Analysis
Bo Zhang, Jiti Gao, Guangming Pan et al.
Design and analysis of randomized trials to estimate spatio-temporally heterogeneous treatment effects
Samuel I. Watson, Thomas A. Smith
Frequency Domain Statistical Inference for High-Dimensional Time Series
Jonas Krampe, Efstathios Paparoditis
Nonparametric data segmentation in multivariate time series via joint characteristic functions
E T McGonigle, H Cho
Summary Modern time series data often exhibit complex dependence and structural changes that are not easily characterized by shifts in ...
Discovering the Network Granger Causality in Large Vector Autoregressive Models
Yoshimasa Uematsu, Takashi Yamagata
High-Dimensional Knockoffs Inference for Time Series Data
Yingying Fan, Jinchi Lv, Chien-Ming Chi et al.
On the Modeling and Prediction of High-Dimensional Functional Time Series
Qiwei Yao, Jinyuan Chang, Xinghao Qiao et al.