4 papers · 1 filter
A Riemannian Factor Model for Manifold-Valued Time Series
Shuo-Chieh Huang, Rong Chen, Yaqing Chen
We propose a Riemannian factor model (RFM), a novel framework for analyzing potentially high-dimensional time series data observed on Riemannian manifolds. Such time series are enc…
Model Selection for Unit-root Time Series with Many Predictors
Shuo-Chieh Huang, Ching-Kang Ing, Ruey S. Tsay
This paper studies model selection for general unit-root time series, including the case with many exogenous predictors. We propose a new model selection algorithm, FHTD, that leve…
Temporal Wasserstein Imputation: A Versatile Method for Time Series Imputation
Shuo-Chieh Huang, Tengyuan Liang, Ruey S. Tsay
Missing data can significantly hamper standard time series analysis, yet they occur frequently in applications. In this paper, we introduce temporal Wasserstein imputation, a novel…
Time Series Forecasting with Many Predictors
Shuo-Chieh Huang, Ruey S. Tsay
We propose a novel approach for time series forecasting with many predictors, referred to as the GO-sdPCA, in this paper. The approach employs a variable selection method known as…