Latest Research in Statistics Theory

Top Research Topics in Statistics Theory

• Statistics Theory — 11 papers
• Random Matrices and Applications — 2 papers
• Machine Learning — 2 papers
• Computation — 2 papers
• Econometrics — 1 papers
• Methodology — 1 papers
• Ecosystem dynamics and resilience — 1 papers
• Statistical Methods and Inference — 1 papers
• Probability — 1 papers
• Bayesian Methods and Mixture Models — 1 papers

Highest-Cited Papers

1. A New Two-Sample Test for Covariance Matrices in High Dimensions: U-Statistics Meet Leading Eigenvalues
2. A two-sample mean vector projection test for high-dimensional Behrens–Fisher problems
3. Finite-Sample Hausdorff Bounds and Hadamard Sensitivity for Regressions with MNAR Covariates
4. Eigenvalue-Decomposition Cost Denoising as an Alternative to Predict-then-Optimize for Shortest-Path Problems
5. Generalised Covariances and Correlations
6. Gaussian Comparison Theorems for High-Dimensional Posterior Inference
7. Unrestricted conditional maximum likelihood estimation for a Fréchet regression model
8. Locally Weighted Unified Shape Function and the One-to-One Correspondence with Regime Boundaries: Multi-Regime Local Peak Correspondence, Population Limit Geometry, and the Pseudo-Peak Phenomenon of Global Splitting
9. A class of nonparametric homogeneity tests on the circle
10. Bernstein-von Mises theorem for sparse generalized linear models
11. Proportional-limit asymptotics for Diaconis-Ylvisaker-penalised logistic regression with fitted intercept
12. Optimal estimation for Functional Linear Regression with Noisy Discretized Data
13. Geometric Fluctuations of the $\sinΘ$ Distance in High-Dimensional Principal Subspace Estimation
14. Normal approximation for U-statistics with cross-sectional dependence
15. Low-Rank and Sparse Drift Estimation for High-Dimensional Lévy-Driven Ornstein--Uhlenbeck Processes
16. Pollak's Minimax Quickest Change Detection: Non-Asymptotic Optimality
17. Scalable Bernoulli Factory MCMC for Intractable Marginalised Posteriors
18. A Unified Descriptive-Complexity Framework for Model Selection under Correlated Designs
19. Estimating the Number of Components in Finite Mixture Models via Variational Approximation
20. Kernelized Stein Discrepancy for Goodness-of-Fit Tests and Stein Sampling in R