Huiyan Sang
Affiliations: | Texas A & M University, College Station, TX, United States |
Area:
Statistics, Nanotechnology, Environmental SciencesGoogle:
"Huiyan Sang"
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Publications
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| Zhong Y, Sang H, Cook SJ, et al. (2022) Sparse spatially clustered coefficient model via adaptive regularization. Computational Statistics & Data Analysis. 107581 |
| Shin YE, Sang H, Liu D, et al. (2019) Autologistic Network Model on Binary Data for Disease Progression Study. Biometrics |
| Zhang B, Sang H, Huang JZ. (2019) Smoothed Full-Scale Approximation of Gaussian Process Models for Computation of Large Spatial Datasets Statistica Sinica |
| Li F, Sang H. (2019) Spatial Homogeneity Pursuit of Regression Coefficients for Large Datasets Journal of the American Statistical Association. 114: 1050-1062 |
| Li F, Sang H, Jing Z. (2017) Quantify the continuous dependence of SST-turbulent heat flux relationship on spatial scales Geophysical Research Letters. 44: 6326-6333 |
| Tapia G, Elwany AH, Sang H. (2016) Prediction of porosity in metal-based additive manufacturing using spatial Gaussian process models Additive Manufacturing. 12: 282-290 |
| Genton MG, Padoan SA, Sang H. (2015) Multivariate max-stable spatial processes Biometrika. 102: 215-230 |
| Zhang B, Konomi BA, Sang H, et al. (2015) Full scale multi-output Gaussian process emulator with nonseparable auto-covariance functions Journal of Computational Physics. 300: 623-642 |
| Zhang B, Sang H, Huang JZ. (2014) Full-scale approximations of spatio-temporal covariance models for large datasets Statistica Sinica. 99 |
| Konomi BA, Sang H, Mallick BK. (2014) Adaptive Bayesian Nonstationary Modeling for Large Spatial Datasets Using Covariance Approximations Journal of Computational and Graphical Statistics. 23: 802-829 |