Yu Yue

Education

Ph.D., Statistics, University of Missouri Columbia MO

M.A., Statistics, University of Missouri Columbia MO

B.S., Statistics, Shanghai University of Finance and Economics Shanghai China

Books

Yue, Y., Wang, X., & Faraway, J. (2018). Bayesian Regression Modeling with INLA. Florida, USA, Chapman & Hall/CRC.

Journal Articles

(2024). ANOPOW for Replicated Nonstationary Time Series In Experiments. Annals of Applied Statistics, 18(1). 328-349.

Rad, K. R., Yue, Y., & Mejia, A. F. (2023). Scalable Parameter-free Bayesian Trend Filtering on Large Graphs. Journal of Machine Learning Research,

Mejia, A. F., Bolin, D., Yue, Y., Wang, J., Caffo, B. S., & Beth Nebel, M. (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.

Spencer, D., Yue, Y., Bolin, D., Ryan, S., & Mejia, A. F. (2022). Spatial Bayesian GLM on the cortical surface produces reliable task activations in individuals and groups. NeuroImage, 249.

Hegyi, A., Csala, D., Kovács, B., Péter, A., Liew, B., Yue, Y., Finni, T., Tihanyi, J., & Cronin, N. (2021). Superimposing hip extension on knee flexion evokes higher activation in biceps femoris than knee flexion alone. Journal of Electromyography and Kinesiology, 58. 102541.

Mejia, A. F., Yue, Y., Bolin, D., Lindgren, F., & Lindquist, M. (2020). A Bayesian General Linear Modeling Approach to Cortical Surface fMRI Data Analysis. Journal of the American Statistical Association , 115(530). 501-520.

Liew, B. X., Yue, Y., Cescon, C., Barbero, M., & Falla, D. (2019). Influence of Experimental Pain on the Spatio-temporal Activity of Upper T Trapezius During Dynamic Lifting – An Investigation using Bayesian Spatio- temporal ANOVA. Journal of Electromyography and Kinesiology, 48. 1-8.

Yue, Y., Bolin, D., Rue, H., & Wang, X. (2019). Bayesian Generalized Two-way ANOVA Modeling for Functional Data Using INLA. Statistica Sinica, 29. 741-767.

Gu, A., Yue, Y., Kim, J., & Argulian, E. (2018). The Burden of Modifiable Risk Factors in Newly Defined Categories of Blood Pressure. The American Journal of Medicine, 131(11). 1349–1358.e5.

Gu, A., Yue, Y., Desai, R., & Argulian, E. (2017). Racial and Ethnic Differences in Antihypertensive Medication Use and Blood Pressure Control among US Adults with Hypertension: The National Health and Nutrition Examination Survey, 2003 to 2012. Circulation: Cardiovascular Quality and Outcomes, 10(1).

Gu, A., Yue, Y., & Argulian, E. (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.

Yue, Y., & Wang, X. (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.

Hong, H., Yue, Y., & Pulak, G. (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.

Yue, Y., & Loh, J. (2015). Variable Selection for Inhomogeneous Spatial Point Process Models. The Canadian Journal of Statistics, 43(2). 288-305.

Yue, Y., & Wang, X. (2014). Spatial Gaussian Markov Random Fields: Modeling, Applications and Efficient Computations. Journal of Biometrics and Biostatistics , 5(e128).

Yue, Y., Simpson, D., Lindgren, F., & Rue, H. (2014). Bayesian Adaptive Smoothing Spline using Stochastic Differential Equations. Bayesian Analysis, 9(2). 397-424.

Waldmann, E., Kneib, T., Yue, Y., Lang, S., & Flexeder, C. (2013). Bayesian Semiparametric Additive Quantile Regression. Statistical Modeling, 13(3). 223-252.

Yue, Y., & Loh, J. (2013). Bayesian Nonparametric Estimation of Pair Correlation Function for Inhomogeneous Spatial Point Processes. Journal of Nonparametric Statistics, 25(2). 463-474.

Yue, Y., & Hong, H. (2012). Bayesian Tobit Quantile Regression Model for Medical Expenditure Panel Survey Data. Statistical Modeling, 12(4). 323-346.

Yue, Y., Speckman, P., & Sun, D. (2012). Priors for Bayesian Adaptive Spline Smoothing. Annals of the Institute of Statistical Mathematics, 64(3). 577-613.

Yue, Y., Lindquist, M., & Loh, J. M. (2012). Meta-analysis of Functional Neuroimaging Data using Bayesian Nonparametric Binary Regression. Annals of Applied Statistics, 6(2). 697-718.

Yue, Y., & Loh, J. M. (2011). Bayesian Semiparametric Intensity Estimation for Inhomogeneous Spatial Point Processes. Biometrics, 67. 937-946.

Yue, Y., & Rue, H. (2011). Bayesian Inference for Additive Mixed Quantile Regression Models. Computational Statistics and Data Analysis, 55. 84-96.

Yue, Y., Loh, J. M., & Lindquist, M. (2010). Adaptive Spatial Smoothing of fMRI Images. Statistics and Its Interface, 3. 3-13.

Rouder, J., Yue, Y., Speckman, P. L., Pratte, M., & Province, J. (2010). Gradual Growth versus Shape Invariance in Perceptual Decision Making. Psychological Review, 117(4). 1267-1274.

Yue, Y., & Speckman, P. (2010). Nonstationary Spatial Gaussian Markov Random Fields. Journal of Computational and Graphical Statistics, 19(1). 96-116.

Presentations

Yue, Y., Bolin, D., Rue, H., & Wang, X. (2018, March 31). Bayesian ANOVA Modeling for Functional Data. ENAR Spring Meeting. Atlanta, GA

Yue, Y., Mejia, A., Bolin, D., Lindgren, F., & Lindquist, M. (2018, June 30). A Bayesian GLM Approach to Cortical Surface fMRI Data Analysis. ICSA 2018 Applied Statistics Symposium. New Brunswick, NJ: International Chinese Statistical Association.

Yue, Y., Mejia, A., Bolin, D., & Lindquist, M. (2018, August 31). A Bayesian GLM Approach to Cortical Surface fMRI Data Analysis. Joint Statistical Meetings. Vancouver, BC, Canada

Yue, Y., Mejia, A., Bolin, D., & Lindquist, M. (2016, August 31). A Bayesian General Linear Modeling Approach to Cortical Surface fMRI Data Analysis. Challenges and Advances on Big Data in Neuroimaging Conference. Cleveland, OH

Yue, Y., Bolin, D., Rue, H., & Wang, X. (2016, August 31). Bayesian ANOVA Modeling for Functional Data. Joint Statistical Meetings. Chicago, IL

Yue, Y., Bolin, D., Rue, H., & Wang, X. (2016, August 31). Bayesian ANOVA Modeling for Functional Data. Workshop on Geometry and Stochastic of Nonlinear, Functional and Graph Data. Bornholm, Denmark

Yue, Y., Bolin, D., Rue, H., & Wang, X. (2015, November 12). Bayesian ANOVA Modeling for Functional Data. Columbia, SC: Department of Statistics, University of South Carolina.

Yue, Y., Lindquist, M., Bolin, D., Lindgren, F., Simpson, D., & Rue, H. (2014, August 31). Bayesian General Linear Modeling Approach for fMRI Data Analysis. Joint Statistical Meetings. Boston, MA, USA: American Statistical Association.

Yue, Y., Lindquist, M., Bolin, D., Lindgren, F., Simpson, D., & Rue, H. (2013, September 30). Bayesian General Linear Model for fMRI Data. Frontiers in Methodological and Applied Statistics: A Celebration of 50 years of MUs Department of Statistics. Columbia, MO: University of Missouri.

Yue, Y., Simpson, D., Lindgren, F., & Rue, H. (2012, July 31). Bayesian Adaptive Smoothing Spline Using Stochastic Differential Equations. The Joint Statistical Meetings. San Diego, CA, USA

Yue, Y., Lindquist, M., Bolin, D., Lindgren, F., Simpson, D., & Rue, H. (2012, November 30). Bayesian General Linear Model for fMRI Data. Newark, NJ: New Jersey Institute of Technology.

Yue, Y., Lindquist, M., Bolin, D., Lindgren, F., Simpson, D., & Rue, H. (2012, December 31). Bayesian General Linear Model for fMRI Data. University of Miami Spatial Statistics Conference. Miami, FL: University of Miami.

Yue, Y., Lindquist, M., & Loh, J. (2012, June 30). Meta-analysis of Functional Neuroimaging Data using Bayesian Nonparametric Binary Regression. The Second International Biostatistics Workshop of Jilin University. Changchun, Jilin, China: Jilin University.

Yue, Y., Lindquist, M., & Loh, J. (2012, January 31). Meta-analysis of Functional Neuroimaging Data using Bayesian Nonparametric Binary Regression. Yorktown Heights, NY: IBM Waterson Research Center.

Yue, Y., Simpson, D., Lindgren, F., & Rue, H. (2012, June 30). Bayesian Adaptive Smoothing Spline Using Stochastic Differential Equations. The Second Workshop on Bayesian Inference for Latent Gaussian Models with Applications. Trondheim, Norway: Norwegian University of Science and Technology.

Yue, Y., Lindquist, M., & Loh, J. (2011, August 31). Meta-analysis of Functional Neuroimaging Data using Bayesian Nonparametric Binary Regression. The Joint Statistical Meetings. Miami Beach, FL, USA

Yue, Y., & Loh, J. M. (2010, October 31). A Bayesian Semiparametric Model for Inhomogeneous Spatial Point Processes. New Haven, CT: Yale University.

Yue, Y., & Loh, J. M. (2010, September 30). A Bayesian Semiparametric Model for Inhomogeneous Spatial Point Processes. Columbia, MO: University of Missouri.

Yue, Y., & Loh, J. M. (2010, August 31). Bayesian semiparametric intensity estimation for inhomogeneous spatial point processes. The Joint Statistical Meetings. Vancouver, BC, Canada

Yue, Y., & Loh, J. M. (2010, July 31). Bayesian semiparametric intensity estimation for inhomogeneous spatial point processes. The Thirteenth Meeting of New Researchers in Statistics and Probability. Vancouver, BC, Canada

Yue, Y., Speckman, P., & Sun, D. (2009, September 30). Bayesian Adaptive Smoothing for Function Estimation. Washington D.C.: American University.

Yue, Y., Loh, J. M., & Lindquist, M. (2009, August 31). Adaptive Spatial Smoothing of fMRI images. The Joint Statistical Meetings. Washington D.C.

Yue, Y., & Speckman, P. (2008, March 31). Adaptive Gaussian Markov Random Fields for Spatial Modeling. The ENAR Meeting. Arlington, VA

Yue, Y., & Speckman, P. (2007, June 30). Spatially Adaptive Intrinsic Gaussian Markov Random Fields. Southern Regional Council on Statistics Meeting. Richmond, RA

Yue, Y., Speckman, P., & Sun, D. (2007, July 31). Objective Priors for Adaptive Smoothing Splines. The Joint Statistical Meetings. Salt Lake City, UT

Yue, Y., & Speckman, P. (2006, August 31). Bayesian Adaptive Thin-plate Splines. The Joint Statistical Meetings. Seattle, WA

Research Currently in Progess

Yue, Y., & Wang, X.(n.d.). A Variable Selection in Latent Class Analysis. In Progress.

Mejia, A. F., & Yue, Y.(n.d.). BayesfMRI Tutorial. In Progress.

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