Statistics and Computing

Article	Citations
Unrestricted permutation forces extrapolation: variable importance requires at least one more model, or there is no free variable importance	59
Comparing clusterings and numbers of clusters by aggregation of calibrated clustering validity indexes	31
Joint models with multiple longitudinal outcomes and a time-to-event outcome: a corrected two-stage approach	24
Gaussian process learning via Fisher scoring of Vecchia’s approximation	18
Ensemble Kalman inversion: mean-field limit and convergence analysis	17
Imputation and low-rank estimation with Missing Not At Random data	16
High-dimensional changepoint detection via a geometrically inspired mapping	16
Optimal non-negative forecast reconciliation	15
Ensemble slice sampling	15
Optimally adaptive Bayesian spectral density estimation for stationary and nonstationary processes	13
Anomaly and Novelty detection for robust semi-supervised learning	13
Sampling of Bayesian posteriors with a non-Gaussian probabilistic learning on manifolds from a small dataset	13
The turning arcs: a computationally efficient algorithm to simulate isotropic vector-valued Gaussian random fields on the d-sphere	13
Unbiased estimation of the gradient of the log-likelihood in inverse problems	11
Inhomogeneous higher-order summary statistics for point processes on linear networks	11
Analysis of stochastic gradient descent in continuous time	11
Graphical test for discrete uniformity and its applications in goodness-of-fit evaluation and multiple sample comparison	11
Composite likelihood methods for histogram-valued random variables	10
Convergence rates for optimised adaptive importance samplers	10
On the performance of particle filters with adaptive number of particles	10
Implicitly adaptive importance sampling	9
Convergence rates of Gaussian ODE filters	9
Likelihood-free approximate Gibbs sampling	9
Cauchy Markov random field priors for Bayesian inversion	9
Bayesian ODE solvers: the maximum a posteriori estimate	9

A wavelet-based approach for imputation in nonstationary multivariate time series	9
Constrained parsimonious model-based clustering	9
Properties of the stochastic approximation EM algorithm with mini-batch sampling	9
A piecewise deterministic Monte Carlo method for diffusion bridges	9
Bayesian additive regression trees with model trees	9
Multilevel particle filters for the non-linear filtering problem in continuous time	8
Fisher Scoring for crossed factor linear mixed models	8
Accelerating sequential Monte Carlo with surrogate likelihoods	8
Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming	8
Bayesian estimation of the latent dimension and communities in stochastic blockmodels	8
Locally induced Gaussian processes for large-scale simulation experiments	8
Outlier detection in non-elliptical data by kernel MRCD	7
Simulating space-time random fields with nonseparable Gneiting-type covariance functions	7
Parallelized integrated nested Laplace approximations for fast Bayesian inference	7
Scalable Bayesian inference for self-excitatory stochastic processes applied to big American gunfire data	7
Deep state-space Gaussian processes	7
Proximal nested sampling for high-dimensional Bayesian model selection	7
Accelerating Metropolis-within-Gibbs sampler with localized computations of differential equations	7
Consistent online Gaussian process regression without the sample complexity bottleneck	7
Importance sampling for a robust and efficient multilevel Monte Carlo estimator for stochastic reaction networks	7
Unbiased approximation of posteriors via coupled particle Markov chain Monte Carlo	6
Low-rank tensor reconstruction of concentrated densities with application to Bayesian inversion	6
Regularized bi-directional co-clustering	6
A closed-form filter for binary time series	6
Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering	6
Fast incremental expectation maximization for finite-sum optimization: nonasymptotic convergence	6
GP-ETAS: semiparametric Bayesian inference for the spatio-temporal epidemic type aftershock sequence model	6
Parsimonious hidden Markov models for matrix-variate longitudinal data	6
An apparent paradox: a classifier based on a partially classified sample may have smaller expected error rate than that if the sample were completely classified	6
Stochastic approximation cut algorithm for inference in modularized Bayesian models	6
Automatic Zig-Zag sampling in practice	6
Fast generation of Gaussian random fields for direct numerical simulations of stochastic transport	6
High-dimensional VAR with low-rank transition	6
Optimal scaling of random walk Metropolis algorithms using Bayesian large-sample asymptotics	5
A robust and efficient algorithm to find profile likelihood confidence intervals	5
An adaptive MCMC method for Bayesian variable selection in logistic and accelerated failure time regression models	5
Point process simulation of generalised inverse Gaussian processes and estimation of the Jaeger integral	5
Wavelet-based robust estimation and variable selection in nonparametric additive models	5
On the identifiability of Bayesian factor analytic models	5
Variational Bayes on manifolds	5
Robust fitting for generalized additive models for location, scale and shape	5
A comparison of likelihood-free methods with and without summary statistics	5
Efficient stochastic optimisation by unadjusted Langevin Monte Carlo	5
Sequential Bayesian optimal experimental design for structural reliability analysis	5
Efficient importance sampling for large sums of independent and identically distributed random variables	5
A Laplace-based algorithm for Bayesian adaptive design	5
The recursive variational Gaussian approximation (R-VGA)	5
Fitting Matérn smoothness parameters using automatic differentiation	5
Particle-based energetic variational inference	5
Changepoint detection in non-exchangeable data	4

Structure-based hyperparameter selection with Bayesian optimization in multidimensional scaling	4
Bayesian inference for continuous-time hidden Markov models with an unknown number of states	4
Model-based clustering with determinant-and-shape constraint	4
Multilevel estimation of normalization constants using ensemble Kalman–Bucy filters	4
Quantile-distribution functions and their use for classification, with application to naïve Bayes classifiers	4
An explicit split point procedure in model-based trees allowing for a quick fitting of GLM trees and GLM forests	4
Systematic enumeration of definitive screening designs	4
BayesProject: Fast computation of a projection direction for multivariate changepoint detection	4
Performance analysis of greedy algorithms for minimising a Maximum Mean Discrepancy	4
Generalised joint regression for count data: a penalty extension for competitive settings	4
Representative random sampling: an empirical evaluation of a novel bin stratification method for model performance estimation	4
Multi-scale process modelling and distributed computation for spatial data	4
Generalized parallel tempering on Bayesian inverse problems	4
Adaptive iterative Hessian sketch via A-optimal subsampling	4
Markov chain Monte Carlo algorithms with sequential proposals	4
Co-clustering of evolving count matrices with the dynamic latent block model: application to pharmacovigilance	4
Improved inference for areal unit count data using graph-based optimisation	4
Conditionally structured variational Gaussian approximation with importance weights	4
Evaluating Gaussian process metamodels and sequential designs for noisy level set estimation	4
Bayesian numerical methods for nonlinear partial differential equations	4
Inference on high-dimensional implicit dynamic models using a guided intermediate resampling filter	4
Rank-one multi-reference factor analysis	3
A fast and efficient smoothing approach to Lasso regression and an application in statistical genetics: polygenic risk scores for chronic obstructive pulmonary disease (COPD)	3
Robust discrete choice models with t-distributed kernel errors	3
High-dimensional order-free multivariate spatial disease mapping	3
Exploiting low-rank covariance structures for computing high-dimensional normal and Student-t probabilities	3
Model-free global likelihood subsampling for massive data	3
Control variate selection for Monte Carlo integration	3
Parallelizing MCMC sampling via space partitioning	3
Optimal representative sample weighting	3
Uncertainty modelling and computational aspects of data association	3
Bayesian nonparametric priors for hidden Markov random fields	3
Deep mixtures of unigrams for uncovering topics in textual data	3
A SUR version of the Bichon criterion for excursion set estimation	3
Quantile hidden semi-Markov models for multivariate time series	3
Ensemble Kalman filter based sequential Monte Carlo sampler for sequential Bayesian inference	3
On automatic bias reduction for extreme expectile estimation	3
Sampling hierarchies of discrete random structures	3
Robust approach for comparing two dependent normal populations through Wald-type tests based on Rényi’s pseudodistance estimators	3
On some consistent tests of mutual independence among several random vectors of arbitrary dimensions	3
Product-form estimators: exploiting independence to scale up Monte Carlo	3
Adaptation of the tuning parameter in general Bayesian inference with robust divergence	3
Sparse functional partial least squares regression with a locally sparse slope function	3
Classification of periodic arrivals in event time data for filtering computer network traffic	3
Variable selection using a smooth information criterion for distributional regression models	3
Maximum likelihood estimation of the Fisher–Bingham distribution via efficient calculation of its normalizing constant	3
Subsampling sequential Monte Carlo for static Bayesian models	3
Stochastic variational inference for scalable non-stationary Gaussian process regression	2
Sticky PDMP samplers for sparse and local inference problems	2
Optimal classification of Gaussian processes in homo- and heteroscedastic settings	2
Identifiability and parameter estimation of the overlapped stochastic co-block model	2
Generating directed networks with predetermined assortativity measures	2
Erlang mixture modeling for Poisson process intensities	2
Accelerating the estimation of renewal Hawkes self-exciting point processes	2
Stochastic variable metric proximal gradient with variance reduction for non-convex composite optimization	2
Correlation-based sparse inverse Cholesky factorization for fast Gaussian-process inference	2
Bayesian wavelet-packet historical functional linear models	2
Unbalanced distributed estimation and inference for the precision matrix in Gaussian graphical models	2
Matrix completion with nonconvex regularization: spectral operators and scalable algorithms	2
Inference for cluster point processes with over- or under-dispersed cluster sizes	2
GParareal: a time-parallel ODE solver using Gaussian process emulation	2
A simple method for rejection sampling efficiency improvement on SIMT architectures	2
A numerically stable algorithm for integrating Bayesian models using Markov melding	2
Sklar’s Omega: A Gaussian copula-based framework for assessing agreement	2
Selecting the derivative of a functional covariate in scalar-on-function regression	2
Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization	2
Bayesian projection pursuit regression	2
A generalized likelihood-based Bayesian approach for scalable joint regression and covariance selection in high dimensions	2
Stochastic cluster embedding	2
A parallel evolutionary multiple-try metropolis Markov chain Monte Carlo algorithm for sampling spatial partitions	2
Approximate Laplace importance sampling for the estimation of expected Shannon information gain in high-dimensional Bayesian design for nonlinear models	2
Nonnegative Bayesian nonparametric factor models with completely random measures	2
Spatiotemporal blocking of the bouncy particle sampler for efficient inference in state-space models	2
Ensemble sampler for infinite-dimensional inverse problems	2
Semi-automated simultaneous predictor selection for regression-SARIMA models	2
Fast Bayesian inversion for high dimensional inverse problems	2
Importance conditional sampling for Pitman–Yor mixtures	2
Toeplitz Monte Carlo	2
Adaptive random neighbourhood informed Markov chain Monte Carlo for high-dimensional Bayesian variable selection	2
Penalized Cox’s proportional hazards model for high-dimensional survival data with grouped predictors	2

Modal Clustering Using Semiparametric Mixtures and Mode Flattening	2
An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization	2
Quantifying uncertainty with a derivative tracking SDE model and application to wind power forecast data	2
Constrained minimum energy designs	2
A Metropolis-class sampler for targets with non-convex support	2
Efficient EM-variational inference for nonparametric Hawkes process	2
Limitations of the Wasserstein MDE for univariate data	2
Variable selection using conditional AIC for linear mixed models with data-driven transformations	2
Scalable methods for computing sharp extreme event probabilities in infinite-dimensional stochastic systems	2
Limit theory and robust evaluation methods for the extremal properties of GARCH(p, q) processes	2
A random persistence diagram generator	2
Characterization of topic-based online communities by combining network data and user generated content	1
Optimal experimental design for linear time invariant state–space models	1
Biclustering via structured regularized matrix decomposition	1
Learning-based importance sampling via stochastic optimal control for stochastic reaction networks	1
Bayesian learning via neural Schrödinger–Föllmer flows	1
Penalized model-based clustering of complex functional data	1
Tree-structured scale effects in binary and ordinal regression	1
Rate-optimal refinement strategies for local approximation MCMC	1
Variable selection and regularization via arbitrary rectangle-range generalized elastic net	1
Efficient and generalizable tuning strategies for stochastic gradient MCMC	1
Variance reduction for additive functionals of Markov chains via martingale representations	1
An information theoretic approach to post randomization methods under differential privacy	1
Eigenfunction martingale estimating functions and filtered data for drift estimation of discretely observed multiscale diffusions	1
Improving bridge estimators via f-GAN	1
Dimension-independent spectral gap of polar slice sampling	1
Inference of multivariate exponential Hawkes processes with inhibition and application to neuronal activity	1
Scalable computations for nonstationary Gaussian processes	1
Efficient probabilistic reconciliation of forecasts for real-valued and count time series	1
The forward–backward envelope for sampling with the overdamped Langevin algorithm	1
Sequential sampling of junction trees for decomposable graphs	1
Comparing unconstrained parametrization methods for return covariance matrix prediction	1
Bayesian parameter inference for partially observed stochastic differential equations driven by fractional Brownian motion	1
A data-driven and model-based accelerated Hamiltonian Monte Carlo method for Bayesian elliptic inverse problems	1
A Bayesian Fisher-EM algorithm for discriminative Gaussian subspace clustering	1
Modern non-linear function-on-function regression	1
Min–max crossover designs for two treatments binary and poisson crossover trials	1
Multiscale stick-breaking mixture models	1
De-noising boosting methods for variable selection and estimation subject to error-prone variables	1
Accelerating Bayesian inference for stochastic epidemic models using incidence data	1
Statistical depth in abstract metric spaces	1
A fast and calibrated computer model emulator: an empirical Bayes approach	1
The conditional censored graphical lasso estimator	1
Model averaging for support vector classifier by cross-validation	1
Regularizing axis-aligned ensembles via data rotations that favor simpler learners	1
On proportional volume sampling for experimental design in general spaces	1
Uncertainty calibration for probabilistic projection methods	1
Graph matching beyond perfectly-overlapping Erdős–Rényi random graphs	1
Prediction scoring of data-driven discoveries for reproducible research	1
State-dependent importance sampling for estimating expectations of functionals of sums of independent random variables	1
Efficient simulation of p-tempered $$\alpha $$-stable OU processes	1
Estimating time-varying directed neural networks	1
Entropic herding	1
Learning from missing data with the binary latent block model	1
Fast and locally adaptive Bayesian quantile smoothing using calibrated variational approximations	1
Flexible non-parametric regression models for compositional response data with zeros	1
Split Hamiltonian Monte Carlo revisited	1
A Joint estimation approach to sparse additive ordinary differential equations	1
Complexity of zigzag sampling algorithm for strongly log-concave distributions	1
Efficient exponential tilting with applications	1
Truncated Poisson–Dirichlet approximation for Dirichlet process hierarchical models	1
Variational Tobit Gaussian Process Regression	1
On estimating the structure factor of a point process, with applications to hyperuniformity	1
Variational inference with vine copulas: an efficient approach for Bayesian computer model calibration	1
Distributional anchor regression	1
Interpolating log-determinant and trace of the powers of matrix $$\textbf{A} + t\textbf{B}$$	1
LASSO for streaming data with adaptative filtering	1
Conditional particle filters with diffuse initial distributions	1
Non-local spatially varying finite mixture models for image segmentation	1
A branch-and-bound algorithm for the exact optimal experimental design problem	1
Confidence graphs for graphical model selection	1
Optimal design of multifactor experiments via grid exploration	1
Power-law distribution in pieces: a semi-parametric approach with change point detection	1
Generalised likelihood profiles for models with intractable likelihoods	1
Sequential changepoint detection in neural networks with checkpoints	1
Testing symmetry for bivariate copulas using Bernstein polynomials	1
Moments and random number generation for the truncated elliptical family of distributions	1
Efficient reduced-rank methods for Gaussian processes with eigenfunction expansions	1
Automatic search intervals for the smoothing parameter in penalized splines	1
Maximum likelihood estimation of the Weibull distribution with reduced bias	1
Modularized Bayesian analyses and cutting feedback in likelihood-free inference	1
Achieving fairness with a simple ridge penalty	1
Exact simulation of normal tempered stable processes of OU type with applications	1
Updating Variational Bayes: fast sequential posterior inference	1
Point process simulation of generalised hyperbolic Lévy processes	1
A two-stage Bayesian semiparametric model for novelty detection with robust prior information	1
Optimization via Rejection-Free Partial Neighbor Search	1
Uniform calibration tests for forecasting systems with small lead time	1
A Riemannian Newton trust-region method for fitting Gaussian mixture models	1
Real time anomaly detection and categorisation	1
Bayesian A-optimal two-phase designs with a single blocking factor in each phase	1
Estimation of time-varying autoregressive stochastic volatility models with stable innovations	1
Constructing two-level $$Q_B$$-optimal screening designs using mixed-integer programming and heuristic algorithms	1
The limited-memory recursive variational Gaussian approximation (L-RVGA)	1
Sparse logistic functional principal component analysis for binary data	1