See this list of recently published papers by our Department of Statistics and Data Science faculty and graduate students, to find out what research topics our department is working on currently.

To find out what research topics our department is working on currently, you can browse this list of recently published papers by our Department of Statistics and Data Science (DS2) faculty and graduate students. Some titles may be truncated in the header field - please click on the header for the drop-down description of the paper for the complete title, all authors, revision date and abstract. 

Linear Non-Gaussian Component Analysis via Maximum Likelihood (2018); Risk, B., Matteson, D., Ruppert, D. JASA, to appear.

A Unified Theory of Testing and Confidence Regions for High Dimensional Estimating Equations (2018); Neykov M, Ning Y, Liu S. J, and Liu H; Statistical Science

High-Dimensional Inference for Cluster-Based Graphical Models (2018+); C. Eisenach, F. Bunea, Y. Ning and C. Dinicu

Bootstrap Bias Corrections for Ensemble Methods (2018); Giles Hooker and Lucas Mentch; Statistic and Computing, 28(1):77086.

Facilitating high-dimensional transparent classification via empirical Bayes variable selection (2018); Bar, H., Booth, J.G., Liu, K. and Wells, M.T. (2018). Applied Stochastic Models in Business and Industry. 

Experimental Design for Partially Observed Markov Decision Processes (2018); Leifur Thorbergsson and Giles Hooker; Journal of Uncertainty Quantification, 6(2):549-567.

Machine Learning and the Future of Realism (2018); Giles Hooker and Clifford A. Hooker; Spontaneous Generations: A Journal for the History and Philosophy of Science, in press. 

Weak interspecific interactions in a sagebrush steppe: evidence from observations, models, and experiments (2018); Adler, Peter B., Andrew Kleinhesselink, Giles Hooker, Brittany Teller and Stephen P. Ellner; Ecology, 99(7):1621-1632.

PCA-based estimation for functional linear regression with functional responses (2018); Masaaki Imaizumi and Kengo Kato;  Journal of Multivariate Analysis, Vol. 163, 2018, pages 15-36.

A Class of Weighted Estimating Equations for Semi-parametric Transformation Models With Missing Covariates (2018); Ning Y, Yi Y. G and Reid N; Scandinavian Journal of Statistics.

A simple method to construct confidence bands in functional linear regression (2018); Masaaki Imaizumi and Kengo Kato; Statistica Sinica, 2018, to appear.

Valid post-selection inference in high-dimensional approximately sparse quantile regression models (2018); Alexandre Belloni, Victor Chernozhukov, and Kengo Kato; Journal of the American Statistical Association, 2018, to appear.

Testing many moment inequalities (2018); Victor Chernozhuov, Denis Chetverikov, and Kengo Kato; Review of Economic Studies, 2018, to appear. 

An Expanded Modern Coexistence Theory for Empirical Applications (2018); Ellner, Stephen P., Snyder, Robin E., Adler, Peter B. and Giles Hooker, Ecology Letters, in press.

Uniform confidence bands in deconvolution with unknown error distribution (2018); Kengo Kato and Yuya Sasaki; Journal of Econometrics, Vol. 207, 2018, pages 129-161. 

A fast algorithm with minimax optimal guarantees for topic models with an unknown number of topics (2018+); Xin Bing, Florentina Bunea and Marten Wegkamp

Model assisted variable clustering: minimax-optimal recovery and algorithms (2018+); Florentina Bunea, Christophe Giraud, Xi Luo, Martin Royer and Nicolas Verzelen. (Under the revision with the Annals of Statistics)

Adaptive Estimation in Structured Factor Models with Applications to Overlapping Clustering (2017, 2018+); Xin Bing, Florentina Bunea, Yang Ning and Marten Wegkamp. 

Penalized versus constrained generalized eigenvalue problems (2017); Gaynanova I, Booth GJ and Wells TM; Journal of Computational and Graphical Statistics, Vol. 26, No. 2, 379-387.

Adaptive estimation of the rank of the coefficient matrix in high dimensional multivariate response regression models (2017); Xin Bing and Marten Wegkamp. (Under the revision with the Annals of Statistics)

On the pseudolike-lihood inference for semiparametric models with boundary problems (2017); Chen Y, Ning J, Ning Y, Liang K-Y, and Bandeen-Roche K; Biometrika.

High-dimensional quantile regression (2017); Alexandre Belloni, Victor Chernozhukov, and Kengo Kato; Handbook of Quantile Regression (eds. Roger Koenker, Victor Chernozhukov, Xuming He, Limin Peng), 2017, Chapman & Hall/CRC. 

Quantile regression methods for longitudinal data (2017); Antonio Galvao and Kengo Kato; Handbook of Quantile Regression (eds. Roger Koenker, Victor Chernozhukov, Xuming He, Limin Peng), 2017, Chapman & Hall/CRC. 

Testing and Confidence Intervals for High Dimensional Proportional Hazards Model (2017); Fang E. X, Ning Y, and Liu H; Journal of the Royal Statistical Society: Series B.

Central limit theorems and bootstrap in high dimensions (2017); Victor Chernozhkov, Denis Chetverikov, and Kengo Kato; Annals of Probability, Vol. 45, 2017, pages 2309-2352.

A General Theory of Hypothesis Tests and Confidence Regions for Sparse High Dimensional Models (2017). Ning Y, and Liu H; Annals of Statistics.

A Likelihood Ratio Framework for High Dimensional Semiparametric Inference (2017); Ning Y, Zhao T. Q and Liu H; Annals of Statistics.

High Dimensional Semiparametric Latent Graphical Model for Mixed Data (2017); Fan J, Liu H, Ning Y, and Zou H; Journal of the Royal Statistical Society: Series B.

Latent model-based clustering for biological discovery (2018+); Xin Bing, Florentina Bunea, Martin Royer and Jishnu Das. (Under the revision with the Cell Press: iScience)

Weak convergence of stationary empirical processes (2017); Dragan Radulovic and Marten Wegkamp. Journal of Statistical Planning and Inference, 2017.