4 papers
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…
Negative Moment Bounds for Sample Autocovariance Matrices of Stationary Processes Driven by Conditional Heteroscedastic Errors and Their Applications
Hsueh-Han Huang, Ching-Kang Ing, Shu-Hui Yu
We establish a negative moment bound for the sample autocovariance matrix of a stationary process driven by conditional heteroscedastic errors. This moment bound enables us to asym…
High-Dimensional Importance-Weighted Information Criteria: Theory and Optimality
Yong-Syun Cao, Shinpei Imori, Ching-Kang Ing
Imori and Ing (2025) proposed the importance-weighted orthogonal greedy algorithm (IWOGA) for model selection in high-dimensional misspecified regression models under covariate shi…
High-Dimensional Knockoffs Inference for Time Series Data
Chien-Ming Chi, Yingying Fan, Ching-Kang Ing +1
We make some initial attempt to establish the theoretical and methodological foundation for the model-X knockoffs inference for time series data. We suggest the method of time seri…