106 citations · 311 across the 18 of their papers we have counts for
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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…
Inference of Random Effects for Linear Mixed-Effects Models with a Fixed Number of Clusters
Chih-Hao Chang, Hsin-Cheng Huang, Ching-Kang Ing
We consider a linear mixed-effects model with a clustered structure, where the parameters are estimated using maximum likelihood (ML) based on possibly unbalanced data. Inference w…
Mixed domain asymptotics for a stochastic process model with time trend and measurement error
Chih-Hao Chang, Hsin-Cheng Huang, Ching-Kang Ing
We consider a stochastic process model with time trend and measurement error. We establish consistency and derive the limiting distributions of the maximum likelihood (ML) estimato…
Estimation of inverse autocovariance matrices for long memory processes
Ching-Kang Ing, Hai-Tang Chiou, Meihui Guo
This work aims at estimating inverse autocovariance matrices of long memory processes admitting a linear representation. A modified Cholesky decomposition is used in conjunction wi…
Toward optimal model averaging in regression models with time series errors
Tzu-Chang F. Cheng, Ching-Kang Ing, Shu-Hui Yu
Consider a regression model with infinitely many parameters and time series errors. We are interested in choosing weights for averaging across generalized least squares (GLS) estim…
Asymptotic theory of generalized information criterion for geostatistical regression model selection
Chih-Hao Chang, Hsin-Cheng Huang, Ching-Kang Ing
Information criteria, such as Akaike's information criterion and Bayesian information criterion are often applied in model selection. However, their asymptotic behaviors for select…