| Year |
Citation |
Score |
| 2022 |
Zhong Y, Sang H, Cook SJ, Kellstedt PM. Sparse spatially clustered coefficient model via adaptive regularization. Computational Statistics & Data Analysis. 107581. PMID 35919543 DOI: 10.1016/j.csda.2022.107581 |
0.339 |
|
| 2019 |
Shin YE, Sang H, Liu D, Ferguson TA, Song PXK. Autologistic Network Model on Binary Data for Disease Progression Study. Biometrics. PMID 31254387 DOI: 10.1111/biom.13111 |
0.308 |
|
| 2019 |
Zhang B, Sang H, Huang JZ. Smoothed Full-Scale Approximation of Gaussian Process Models for Computation of Large Spatial Datasets Statistica Sinica. DOI: 10.5705/Ss.202017.0008 |
0.495 |
|
| 2019 |
Li F, Sang H. Spatial Homogeneity Pursuit of Regression Coefficients for Large Datasets Journal of the American Statistical Association. 114: 1050-1062. DOI: 10.1080/01621459.2018.1529595 |
0.398 |
|
| 2017 |
Li F, Sang H, Jing Z. Quantify the continuous dependence of SST-turbulent heat flux relationship on spatial scales Geophysical Research Letters. 44: 6326-6333. DOI: 10.1002/2017Gl073695 |
0.367 |
|
| 2016 |
Tapia G, Elwany AH, Sang H. Prediction of porosity in metal-based additive manufacturing using spatial Gaussian process models Additive Manufacturing. 12: 282-290. DOI: 10.1016/J.Addma.2016.05.009 |
0.425 |
|
| 2015 |
Genton MG, Padoan SA, Sang H. Multivariate max-stable spatial processes Biometrika. 102: 215-230. DOI: 10.1093/Biomet/Asu066 |
0.432 |
|
| 2015 |
Zhang B, Konomi BA, Sang H, Karagiannis G, Lin G. Full scale multi-output Gaussian process emulator with nonseparable auto-covariance functions Journal of Computational Physics. 300: 623-642. DOI: 10.1016/J.Jcp.2015.08.006 |
0.421 |
|
| 2014 |
Zhang B, Sang H, Huang JZ. Full-scale approximations of spatio-temporal covariance models for large datasets Statistica Sinica. 99. DOI: 10.5705/Ss.2013.260W |
0.331 |
|
| 2014 |
Konomi BA, Sang H, Mallick BK. Adaptive Bayesian Nonstationary Modeling for Large Spatial Datasets Using Covariance Approximations Journal of Computational and Graphical Statistics. 23: 802-829. DOI: 10.1080/10618600.2013.812872 |
0.515 |
|
| 2013 |
Sang H, Genton MG. Tapered composite likelihood for spatial max-stable models Spatial Statistics. DOI: 10.1016/J.Spasta.2013.07.003 |
0.494 |
|
| 2013 |
Chakraborty A, De S, Bowman KP, Sang H, Genton MG, Mallick BK. An adaptive spatial model for precipitation data from multiple satellites over large regions Statistics and Computing. 1-17. DOI: 10.1007/S11222-013-9439-8 |
0.428 |
|
| 2012 |
Sang H, Huang JZ. A full scale approximation of covariance functions for large spatial data sets Journal of the Royal Statistical Society Series B-Statistical Methodology. 74: 111-132. DOI: 10.1111/J.1467-9868.2011.01007.X |
0.514 |
|
| 2011 |
Sang H, Jun M, Huang JZ. Covariance approximation for large multivariate spatial data sets with an application to multiple climate model errors Annals of Applied Statistics. 5: 2519-2548. DOI: 10.1214/11-Aoas478 |
0.505 |
|
| 2010 |
Sang H, Gelfand AE. Continuous spatial process models for spatial extreme values Journal of Agricultural, Biological, and Environmental Statistics. 15: 49-65. DOI: 10.1007/S13253-009-0010-1 |
0.494 |
|
| 2009 |
Finley AO, Sang H, Banerjee S, Gelfand AE. Improving the performance of predictive process modeling for large datasets. Computational Statistics & Data Analysis. 53: 2873-2884. PMID 20016667 DOI: 10.1016/J.Csda.2008.09.008 |
0.512 |
|
| 2009 |
Latimer AM, Banerjee S, Sang H, Mosher ES, Silander JA. Hierarchical models facilitate spatial analysis of large data sets: a case study on invasive plant species in the northeastern United States. Ecology Letters. 12: 144-54. PMID 19143826 DOI: 10.1111/J.1461-0248.2008.01270.X |
0.489 |
|
| 2009 |
Sang H, Gelfand AE. Hierarchical modeling for extreme values observed over space and time Environmental and Ecological Statistics. 16: 407-426. DOI: 10.1007/S10651-007-0078-0 |
0.499 |
|
| 2008 |
Banerjee S, Gelfand AE, Finley AO, Sang H. Gaussian predictive process models for large spatial data sets. Journal of the Royal Statistical Society. Series B, Statistical Methodology. 70: 825-848. PMID 19750209 DOI: 10.1111/J.1467-9868.2008.00663.X |
0.542 |
|
| 2008 |
Sang H, Gelfand AE, Lennard C, Hegerl G, Hewitson B. Interpreting self-organizing maps through space-time data models Annals of Applied Statistics. 2: 1194-1216. DOI: 10.1214/08-Aoas174 |
0.322 |
|
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