| Choosing between methods of combining p-values |
14 |
| Multivariate output analysis for Markov chain Monte Carlo |
12 |
| Gene hunting with hidden Markov model knockoffs |
11 |
| High-dimensional peaks-over-threshold inference |
10 |
| A non-model-based approach to bandwidth selection for kernel estimators of spatial intensity functions |
9 |
| Nonparametric independence testing via mutual information |
8 |
| Identifying causal effects with proxy variables of an unmeasured confounder |
7 |
| Unbiased Hamiltonian Monte Carlo with couplings |
7 |
| Asymptotic properties of approximate Bayesian computation |
7 |
| Decompositions of dependence for high-dimensional extremes |
7 |
| Miscellanea Calibrating general posterior credible regions |
7 |
| Approximate Bayesian inference under informative sampling |
6 |
| On the asymptotic efficiency of approximate Bayesian computation estimators |
6 |
| Covariate association eliminating weights: a unified weighting framework for causal effect estimation |
6 |
| The debiased Whittle likelihood |
6 |
| Accounting for unobserved covariates with varying degrees of estimability in high-dimensional biological data |
6 |
| Theoretical limits of microclustering for record linkage |
5 |
| Kinetic energy choice in Hamiltonian/hybrid Monte Carlo |
5 |
| Frechet analysis of variance for random objects |
5 |
| Two-sample tests of high-dimensional means for compositional data |
5 |
| Kernel-based covariate functional balancing for observational studies |
5 |
| Randomization tests of causal effects under interference |
5 |
| General Bayesian updating and the loss-likelihood bootstrap |
5 |
| Uniformly minimum variance conditionally unbiased estimation in multi-arm multi-stage clinical trials |
5 |
| Robust and consistent variable selection in high-dimensional generalized linear models |
4 |
| A semiparametric extension of the stochastic block model for longitudinal networks |
4 |
| Sequential rerandomization |
4 |
| A test of weak separability for multi-way functional data, with application to brain connectivity studies |
4 |
| Symmetric rank covariances: a generalized framework for nonparametric measures of dependence |
4 |
| Variance estimation in the particle filter |
4 |
| Estimating the error variance in a high-dimensional linear model |
4 |
| Regression-assisted inference for the average treatment effect in paired experiments |
4 |
| Constructing dynamic treatment regimes over indefinite time horizons |
4 |
| Design of order-of-addition experiments |
4 |
| Classification of functional fragments by regularized linear classifiers with domain selection |
4 |
| Rejoinder: Gene hunting with hidden Markov model knockoffs' |
3 |
| Extremal behaviour of aggregated data with an application to downscaling |
3 |
| Constrained likelihood for reconstructing a directed acyclic Gaussian graph |
3 |
| Recovering covariance from functional fragments |
3 |
| Generalized meta-analysis for multiple regression models across studies with disparate covariate information |
3 |
| Simultaneous control of all false discovery proportions in large-scale multiple hypothesis testing |
3 |
| Asymptotic normality of interpoint distances for high-dimensional data with applications to the two-sample problem |
3 |
| On the connection between maximin distance designs and orthogonal designs |
3 |
| A convex formulation for high-dimensional sparse sliced inverse regression |
3 |
| Testing independence for multivariate time series via the auto-distance correlation matrix |
3 |
| Asymptotic inference of causal effects with observational studies trimmed by the estimated propensity scores |
3 |
| Robust estimation of high-dimensional covariance and precision matrices |
3 |
| Asymptotic post-selection inference for the Akaike information criterion |
3 |
| On overfitting and post-selection uncertainty assessments |
3 |
| Scalar-on-image regression via the soft-thresholded Gaussian process |
3 |
