24 citations · 61 across the 9 of their papers we have counts for
10 papers
Assessing Spatial Stationarity and Segmenting Spatial Processes into Stationary Components
ShengLi Tzeng, Bo-Yu Chen, Hsin-Cheng Huang
In this research, we propose a novel technique for visualizing nonstationarity in geostatistics, particularly when confronted with a single realization of data at irregularly space…
Spatially Adaptive Calibrations of AirBox PM Data
ShengLi Tzeng, Chi-Wei Lai, Hsin-Cheng Huang
Two networks are available to monitor PM in Taiwan, including the Taiwan Air Quality Monitoring Network (TAQMN) and the AirBox network. The TAQMN, managed by Taiwan's Envir…
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…
Vector Autoregressive Models with Spatially Structured Coefficients for Time Series on a Spatial Grid
Yuan Yan, Hsin-Cheng Huang, Marc G. Genton
We propose a parsimonious spatiotemporal model for time series data on a spatial grid. Our model is capable of dealing with high-dimensional time series data that may be collected…
False Discovery Rates to Detect Signals from Incomplete Spatially Aggregated Data
Hsin-Cheng Huang, Noel Cressie, Andrew Zammit-Mangion +1
There are a number of ways to test for the absence/presence of a spatial signal in a completely observed fine-resolution image. One of these is a powerful nonparametric procedure c…
Regularized Spatial Maximum Covariance Analysis
Wen-Ting Wang, Hsin-Cheng Huang
In climate and atmospheric research, many phenomena involve more than one meteorological spatial processes covarying in space. To understand how one process is affected by another,…
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…
Multi-Resolution Spatial Random-Effects Models for Irregularly Spaced Data
ShengLi Tzeng, Hsin-Cheng Huang
The spatial random-effects model is flexible in modeling spatial covariance functions, and is computationally efficient for spatial prediction via fixed rank kriging. However, the…
Regularized Principal Component Analysis for Spatial Data
Wen-Ting Wang, Hsin-Cheng Huang
In many atmospheric and earth sciences, it is of interest to identify dominant spatial patterns of variation based on data observed at locations and time points with the po…
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…