Research

Research Interests

My research interests include

• Post-selection inference / selective inference

• Scalable algorithms for massive data sets

• Multivariate analysis and dimensionality reduction in large data sets

• Methods for stable estimation and inference in heavy-tailed data

• Ecological statistics and microecology data

Current students

• Yixiang Luo

• Drew Nguyen

Former students

• Johnny Hong 2020 (co-advised with Perry de Valpine)

• Kenneth Hung 2019

• Xiao Li (co-advised with Bin Yu) 2021

• Sara Stoudt (co-advised with Perry de Valpine) 2020

• Chiao-Yu Yang (co-advised with Michael Jordan) 2021

Publications and Preprints

Multiple testing with structure

• AdaPT-GMM: Powerful and robust covariate-assisted multiple testing (video) (slides), Patrick Chao and William Fithian, 2021, preprint.

• BONuS: Multiple multivariate testing with a data-adaptive test statistic, Chiao-Yu Yang, Lihua Lei, Nhat Ho, and William Fithian, 2021, preprint.

• Smoothed nested testing on directed acyclic graphs, Jackson Loper, Lihua Lei, William Fithian, and Wesley Tansey, 2022, Biometrika.

• STAR: A general interactive framework for FDR control under structural constraints, Lihua Lei, Aaditya Ramdas, and William Fithian, 2020, Biometrika.

• Family learning: nonparametric statistical inference with parametric efficiency, William Fithian and Daniel Ting, 2017, preprint.

• AdaPT: An interactive procedure for multiple testing with side information (video) (slides), Lihua Lei and William Fithian, 2018, JRSS-B.

• Power of Ordered Hypothesis Testing, Lihua Lei and William Fithian, 2016, ICML.

Theory of multiple testing

• Locally Simultaneous Inference. Tijana Zrnic and William Fithian, 2022. Preprint.

• Asymptotically Optimal Knockoff Statistics via the Masked Likelihood Ratio. Asher Spector and William Fithian, 2022. Preprint.

• Improving knockoffs with conditional calibration. Yixiang Luo, William Fithian, and Lihua Lei, 2022. Preprint.

• The edge of discovery: Controlling the local false discovery rate at the margin. Jake Soloff, Daniel Xiang, and William Fithian, 2024, Annals of Statistics (to appear).

• Whiteout: when do fixed-X knockoffs fail? (video) (slides), Xiao Li and William Fithian, 2021. Preprint.

• Conditional calibration for false discovery rate control under dependence (video) (slides), William Fithian and Lihua Lei, 2022, Annals of Statistics.

• Optimality of the max test for detecting sparse signals with Gaussian or heavier tail, Xiao Li and William Fithian, 2020. Preprint.

Conditional post-selection inference and replicability

• Statistical Methods for Replicability Assessment, Kenneth Hung and William Fithian, 2020, Annals of Applied Statistics.

• Rank Verification for Exponential Families, Kenneth Hung and William Fithian, 2019, Annals of Statistics.

• Adaptive Sequential Model Selection (github), William Fithian, Jonathan Taylor, Robert Tibshirani, and Ryan Tibshirani, 2015. Under revision.

• Optimal Inference After Model Selection (github), William Fithian, Dennis Sun, and Jonathan Taylor, 2014. Preprint.

• Selection Adjusted Confidence Intervals with More Power to Determine the Sign, (pdf) Asaf Weinstein, William Fithian, and Yoav Benjamini, 2012, JASA.

Scalable Algorithms for Large Data Sets

• Local Case-Control Sampling: Efficient Subsampling in Imbalanced Data Sets, William Fithian and Trevor Hastie, 2014, Annals of Statistics.

Multivariate Analysis and Dimension Reduction

• Multiple Correspondence Analysis and the Multilogit Bilinear Model, (arXiv) William Fithian and Julie Josse, 2017. Journal of Multivariate Analysis.

• Scalable Convex Methods for Flexible Low-Rank Matrix Modeling, William Fithian and Rahul Mazumder, 2018, Statistical Science.

Microbiome Data and Ecological Statistics

• Nonparametric Identifiability in Species Distribution and Abundance Models: Why it Matters and How to Diagnose a Lack of it Using Simulation, Sara Stoudt, Perry de Valpine, William Fithian, 2023, Journal of Statistical Theory and Practice.

• To rarefy or not to rarefy: robustness and efficiency trade-offs of rarefying microbiome data, Johnny Hong, Ulas Karaoz, Perry de Valpine, and William Fithian. 2022, Bioinformatics.

• Bias Correction in Species Distribution Models: Pooling Survey and Collection Data for Multiple Species, (pdf) William Fithian, Jane Elith, Trevor Hastie, and David A. Keith. 2014, Methods in Ecology and Evolution.

• Finite Sample Equivalence in Statistical Models for Presence-Only Data, William Fithian and Trevor Hastie, 2013, Annals of Applied Statistics.

• Inference from Presence-Only Data: the Ongoing Controversy, (pdf) Trevor Hastie and William Fithian, 2013, Ecography.

Miscellaneous

• Framework for in vivo T cell screens, Lauren E. Milling et al. 2024, Journal of Experimental Medicine.

• Data Augmentation via Levy Processes, Stefan Wager, William Fithian, and Percy Liang, 2016. Chapter in Advanced Structured Prediction.

• Semiparametric Exponential Families for Heavy-Tailed Data, William Fithian and Stefan Wager, 2015, Biometrika.

• Altitude Training: Strong Bounds for Single-Layer Dropout, Stefan Wager, William Fithian, Sida Wang, and Percy Liang. 2014, NIPS.

• Effective Degrees of Freedom: A Flawed Metaphor, Lucas Janson, William Fithian, and Trevor Hastie, 2015, Biometrika.