Publications

  1. Rad, Yue, Mejia (2023). “Scalable Parameter-free Bayesian Trend Filtering on Large Graphs.”  (In revision)
  2. Li, Yue, Bruce (2023). “ANOPOW for Replicated Nonstationary Time Series In Experiments.”  The Annals of Applied Statistics (accepted).
  3. Mejia, Bolin, Yue, Nebel, Wang, Caffo (2023). “Template Independent Component Analysis with Spatial Priors for Accurate Subject-Level Brain Network Estimation and Inference.” Journal of Computational and Graphical Statistics, 32:2,413-433. 
  4. Spencer, Yue, Bolin, Ryan, and Mejia (2022). “Spatial Bayesian GLM on the Cortical Surface Produces Reliable Task Activations in Individuals and Groups.” NeuroImage, 249, 118908.
  5. Mejia, Yue, Bolin and Lindquist (2020). “A Bayesian General Linear Modeling Approach to Cortical Surface fMRI Data Analysis.” Journal of the American Statistical Association, 115, 501-520.
  6. Liew, Yue, Cescon, Barbero, Falla (2019). “Influence of Experimental Pain on the Spatio-temporal Activity of Upper Trapezius during Dynamic Lifting – An Investigation using Bayesian Spatio-temporal ANOVA.” Journal of Electromyography and Kinesiology, 48, 1-8.
  7. Yue, Bolin, Rue, and Wang (2019). “Bayesian Generalized Two-way ANOVA Modeling for Functional Data Using INLA.” Statistica Sinica, 29, 741-767.
  8. Gu, Yue, Kim and Argulian (2018). “The Burden of Modifiable Risk Factors in Newly Defined Categories of Blood Pressure” The American Journal of Medicine, 131(11), 1349-1358.e5.
  9. Gu, Yue, Desai and Argulian (2017).“Racial and Ethnic Differences in Antihypertensive Medication Use and Blood Pressure Control among United States Adults with Hypertension: The National Health and Nutrition Examination Survey, 2003 to 2012” Circulation: Cardiovascular Quality and Outcomes doi: 10.1161/CIRCOUTCOMES.116.003166
  10. Gu, Yue, and Argulian (2016). “Age Differences in Treatment and Control of Hypertension in US Physician Offices, 2003-2010: A Serial Cross-sectional Study” The American Journal of Medicine, 129, 50-58.
  11. Yue and Wang (2016). “Bayesian Inference for Generalized Linear Mixed Models with Predictors Subject to Detection Limits: An Approach that Leverages Information from Auxiliary Variables.” Statistics in Medicine, 35, 1689-1705.
  12. Yue and Loh (2015). “Variable Selection for Inhomogeneous Spatial Point Process Models.” The Canadian Journal of Statistics, 43(2), 288-305.
  13. Hong, Yue, and Gosh (2015). “Bayesian Estimation of Long-Term Health Consequences of Obese and Normal-Weight Elderly.” Journal of the Royal Statistical Society: Series A (Statistics in Society), 178(3), 725-739.
  14. Yue and Wang (2014). “Spatial Gaussian Markov Random Fields: Modeling, Applications and Efficient Computations.” Journal of Biometrics and Biostatistics, 5:e128. doi: 10.4172/2155-6180.1000e128.
  15. Yue, Simpson, Lindgren and Rue (2014). “Bayesian Adaptive Smoothing Spline using Stochastic Differential Equations.” Bayesian Analysis, 9(2), 397-424.
  16. Waldmann, Kneib, Yue, Lang and Flexeder (2013). “Bayesian Semiparametric Additive Quantile Regression.” Statistical Modeling, 13(3), 223-252.
  17. Yue and Loh (2013). “Bayesian Nonparametric Estimation of Pair Correlation Function for Inhomogeneous Spatial Point Processes.” Journal of Nonparametric Statistics, 25(2), 463-474.
  18. Yue and Hong (2012). “Bayesian Tobit Quantile Regression Model for Medical Expenditure Panel Survey Data.” Statistical Modeling, 12(4), 323-346.
  19. Yue, Lindquist and Loh (2012). “Meta-analysis of Functional Neuroimaging Data using Bayesian Nonparametric Binary Regression.” The Annals of Applied Statistics, 6(2), 697- 718.
  20. Yue, Speckman, and Sun (2012). “Priors for Bayesian Adaptive Spline Smoothing.” Annals of the Institute of Statistical Mathematics, 64(3), 577-613.
  21. Yue and Loh (2011). “Bayesian Semiparametric Intensity Estimation for Inhomogeneous Spatial Point Processes.” Biometrics, 67, 937-946.
  22. Yue and Rue (2011). “Bayesian Inference for Additive Mixed Quantile Regression Models.” Computational Statistics and Data Analysis, 55, 84-96.
  23. Rouder, Yue, Speckman, Pratte, and Province (2010). “Gradual Growth Versus Shape Invariance in Perceptual Decision Making.” Psychological Review, 117(4), 1267-1274.
  24. Yue, Loh and Lindquist (2010). “Adaptive Spatial Smoothing of fMRI Images.” Statistics and Its Interface, 3, 3-13.
  25. Yue and Speckman (2010). “Nonstationary Spatial Gaussian Markov Random Fields.” Journal of Computational and Graphical Statistics, 19(1), 96-116.