The Functional Data Reading Group meets every Friday at 1:00 pm in SAS 5202. Discussions may include recent publications, book chapters, student research presentations, and practice sessions for upcoming conferences. An up-to-date list of previous and upcoming topics can be found here. Slides will be available on this page after the presentation date.
Spring 2024
- Jan 12: Samsul “Supervised low-rank approximation of high-dimensional multivariate functional data via tensor decomposition”.
- Jan 19: Xiaoxia “Categorical Functional Data Analysis with Application to Social Media”
- Feb 2: Jake “Testing For Susceptibility to Interaction with Automated Accounts“
- Feb 9 : Michael “Density Dependent Imputation of Functional Data with Informative Censoring”
- Feb 16 : Xiaoxia “Restricted Likelihood Ratio Test for Categorical Functional Data from Social Media”
- March 1 : Alvin “Two Environmental Hazard Applications: Flood Risk and PFAS Pollution“
- March 8 (Faculty meeting), March 15 (Spring Break) cancelled
- March 22 : Charlie “Improved Goodness-of-fit Test of Covariance for Sparse Functional Data“
- March 29 : Alex ““
- April 5 : WenYi “Joint Model for Survival and Multivariate Sparse Functional Data for Multiple Cohorts of Alzheimer’s Disease“
- April 12 : Samsul “Modern methods for the next generation of functional data“
- April 19 : Charlie “Functional Data Analysis with Informative Censoring“
Spring 2023
- Jan 20: Jake and Michael “A geometric approach to maximum likelihood estimation of the functional principal components from sparse longitudinal data” by Peng, Jie, and Debashis Paul. Journal of Computational and Graphical Statistics 18.4 (2009): 995-1015.
- Feb 03: Michael and Xiaoxia “Functional data analysis for longitudinal data with informative observation times” by Caleb Weaver, Lou Xiao, and Wenbin Lu. Biometrics (2022).
- Mar 10: Samsul and Alvin “Functional Feature Construction for Individualized Treatment Regimes” by Eric B. Laber and Ana-Maria Staicu. (2018). Journal of the American Statistical Association 113(523). (2018).
- Mar 23: Xiaoxia “A Bayesian multivariate functional model with spatially varying coefficient approach for modeling hurricane track data” by Rekabdarkolaee, H. M., Krut, C., Fuentes, M., & Reich, B. J. Spatial Statistics, 29. (2019).
- Mar 31: Samsul “Guaranteed Functional Tensor Singular Value Decomposition” by Rungang Han, Pixu Shi and Anru R. Zhang. Journal of the American Statistical Association. (2022).
- Apr 21: Alvin and Jake “A Two Sample Distribution-Free Test for Functional Data with Application to a Diffusion Tensor Imaging Study of Multiple Sclerosis” by Pomann GM, Staicu AM, Ghosh S. Journal of the Royal Statistical Society 65(3). (2016).
- Simultaneous decorrelation of matrix time series. by Han, Y., Chen, R., Zhang, C. H., & Yao, Q. (2023). Journal of the American Statistical Association.
- Bayesian Framework for Simultaneous Registration and Estimation of Noisy, Sparse and Fragmented Functional Data by J. Matuk, K. Bharath, O. Chkrebtii, S. Kurtek. Journal of the American Statistical Association, 117(540) (2022).
- “Functional data analysis for dynamical system identification of behavioral processes” by Trail JB, Collins LM, Rivera DE, Li R, Piper ME, Baker TB. Psychol Methods, 19(2) (2014).
- “Modeling time-varying random objects and dynamic networks.” by Dubey, P and Muller HG (2021) . Journal of the American Statistical Association, 1-16.
- “Network functional varying coefficient model.” by Zhu, Xuening, Zhanrui Cai, and Yanyuan Ma. Journal of the American Statistical Association (2021): 1-12.
- “Single-index models with functional connectivity network predictors” by Weaver, C., Xiao, L., & Lindquist, M. A. Biostatistics 24(1) (2023).
- “Sparse single index models for multivariate responses” by Feng, Y., Xiao, L., & Chi, E. C. Journal of Computational and Graphical Statistics, 30(1). (2021).
- “A spatio-temporal model for longitudinal image-on-image regression” by Hazra, A., Reich, B. J., Reich, D. S., Shinohara, R. T., & Staicu, A. M. Stat. Biosci 11. (2019).
Spring 2021
Jan 15: Salil, Samsul, Sukanya and Adam “Predicting Clinical Outcomes in Glioblastoma: An Application of Topological and Functional Data Analysis” by Crawford, Monod, Mukherjee and Rabadán (2019).
Jan 29: “Statistical Analysis of Functions on Surfaces, With an Application to Medical Imaging” by Lila and Aston (2019).
Feb 5: “Prediction, Estimation, and Attribution” by Efron (2020).
Feb 12: “Discussion of “Prediction, Estimation, and Attribution” by Bradley Efron” by Friedman, Hastie and Tibshirani (2020) and “Discussion of the Paper “Prediction, Estimation, and Attribution” by B. Efron” by Candès and Sabatti (2020).
Feb 19: “Comment: When Is It Data Science and When Is It Data Engineering?” by Cressie (2020).
Feb 26: “Rejoinder” by Efron (2020).
Mar 5: “Functional Censored Quantile Regression” by Jiang, Cheng, Yin and Shen (2019).
Mar 12: “Additive Functional Regression for Densities as Responses” by Han, Müller and Park (2019).
Spring 2020
Jan 17: Zekun (Jack) Xu (P1), Alex Long (P2) and Salil Koner (P3), A Spatial Modeling Approach for Linguistic Object Data: Analyzing Dialect Sound Variations Across Great Britain by 2019).
Fall 2017
Aug 25: Md Nazmul Islam, “Modeling sparse generalized longitudinal observations with latent gaussian processes” by Hall, Muller, and Yao (2007).
Sep 1: Stephanie Chen, “Restricted Likelihood Ratio Tests for Functional Effects in the Functional Linear Model” by Swihart, Goldsmith, and Crainiceanu (2014). Slides
Sep 15: Michael Geden, “An anova test for functional data” by Cuevas, Febrero, and Fraiman (2004).
Sep 22: Saebitna Oh, “Two Samples Tests for Functional Data” by Zhang, Peng, and Zhang (2010).
Sep 29: Wanying Ma, “Joint Modeling and Clustering Paired Generalized Longitudinal Trajectories With Application to Cocaine Abuse Treatment Data” by Huang, Li, and Guan (2014).
Oct 13: Meredith King, “A Measure of Directional Outlyingness with Applications to Image Data and Video” by Rousseuw, Raymeakers, and Hubert (2017). Slides