Latest Research in Statistics Theory
27 research papers · 2026 median publication year
Top Research Topics in Statistics Theory
- Methodology — 11 papers
- Statistical Methods and Inference — 5 papers
- Machine Learning — 3 papers
- Statistics Theory — 2 papers
- Machine Learning — 2 papers
- Frailty in Older Adults — 1 papers
- Advanced Causal Inference Techniques — 1 papers
- Neural Networks and Reservoir Computing — 1 papers
- Computer Vision and Pattern Recognition — 1 papers
Highest-Cited Papers
- Integrative Analysis of Heterogeneous Multisource Partly Interval‐Censored Data
- Optimal estimation and goodness-of-fit testing of the mean for sparse longitudinal functional data
- The Impact of the Number and the Size of Clusters on Prediction Performance of the Stratified and the Conditional Shared Gamma Frailty Cox Proportional Hazards Models
- Correcting Boundary Bias and Observation Independence in Bayesian Experimental Design
- Debiased machine learning for combining probability and non-probability survey data
- H‐Likelihood Approach on the Joint Frailty Model for Clustered Bivariate Survival Data
- On a Penalized Likelihood Approach for Joint Modeling of Longitudinal Covariates and Partly Interval‐Censored Data—An Application to the Anti‐PD1 Brain Collaboration Trial
- A data-driven Fourier-mixture neural-network method for density estimation
- Low-Rank Tensor Estimation from Nonlinear Observations: A Unified Framework
- Diagonal Attenuation: A Finite-Sample Correction for PCA
- A Location-Invariant Estimator of Extremal Quantile Treatment Effects for Heavy-Tailed Distributions
- Flexible Transformations for Bayesian Score Calibration
- Approximating Bayesian leave-one-group-out cross-validation
- EM algorithm for change-point additive hazards models with partially interval-censored data
- Online Learning of Functional Principal Component Analysis for Multidimensional Functional Data
- Causal Inference for Heterogeneous Extreme Quantiles with Heavy-Tailed Outcomes
- HyperMC: Multi-Fidelity Hyperparameter Tuning for Stochastic Gradient MCMC
- Estimating dynamic models by matching random features
- Outcome‐Adaptive Lasso for Cox Proportional Hazards Model
- Efficient Inference on High-Dimensional Linear Models with Missing Outcomes