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09/01/2023
Consistency of Lloyd's Algorithm Under Perturbations
In the context of unsupervised learning, Lloyd's algorithm is one of the...
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07/28/2023
Group integrative dynamic factor models for inter- and intra-subject brain networks
This work introduces a novel framework for dynamic factor model-based da...
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07/19/2023
Latent Gaussian dynamic factor modeling and forecasting for multivariate count time series
This work considers estimation and forecasting in a multivariate count t...
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07/19/2023
Dynamic factor and VARMA models: equivalent representations, dimension reduction and nonlinear matrix equations
A dynamic factor model with factor series following a VAR(p) model is sh...
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07/19/2023
Correlation networks, dynamic factor models and community detection
A dynamic factor model with a mixture distribution of the loadings is in...
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01/02/2023
High-dimensional latent Gaussian count time series: Concentration results for autocovariances and applications
This work considers stationary vector count time series models defined v...
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05/27/2021
Thresholding and graphical local Whittle estimation
This work develops non-asymptotic theory for estimation of the long-run ...
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05/26/2021
Block Dense Weighted Networks with Augmented Degree Correction
Dense networks with weighted connections often exhibit a community like ...
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07/19/2020
A Square-Root Second-Order Extended Kalman Filtering Approach for Estimating Smoothly Time-Varying Parameters
Researchers collecting intensive longitudinal data (ILD) are increasingl...
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07/09/2020
Penalized Estimation and Forecasting of Multiple Subject Intensive Longitudinal Data
Intensive Longitudinal Data (ILD) is an increasingly common data type in...
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04/20/2019
Stationary subspace analysis of nonstationary covariance processes: eigenstructure description and testing
Stationary subspace analysis (SSA) searches for linear combinations of t...
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11/01/2018
Latent Gaussian Count Time Series Modeling
This paper develops theory and methods for the copula modeling of statio...
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10/02/2018