92 citations · 185 across the 21 of their papers we have counts for
22 papers
Quantile Vector Autoregression without Crossing
Tomohiro Ando, Tadao Hoshino, Ruey Tsay
This paper considers estimation and model selection of quantile vector autoregression (QVAR). Conventional quantile regression often yields undesirable crossing quantile curves, vi…
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…
Vector AutoRegressive Moving Average Models: A Review
Marie-Christine Düker, David S. Matteson, Ruey S. Tsay +1
Vector AutoRegressive Moving Average (VARMA) models form a powerful and general model class for analyzing dynamics among multiple time series. While VARMA models encompass the Vect…
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…
Supervised Dynamic PCA: Linear Dynamic Forecasting with Many Predictors
Zhaoxing Gao, Ruey S. Tsay
This paper proposes a novel dynamic forecasting method using a new supervised Principal Component Analysis (PCA) when a large number of predictors are available. The new supervised…