Statistics and Computing

Papers
(The median citation count of Statistics and Computing is 1. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-09-01 to 2025-09-01.)
ArticleCitations
Representative random sampling: an empirical evaluation of a novel bin stratification method for model performance estimation115
Learning from missing data with the binary latent block model29
Automated generation of initial points for adaptive rejection sampling of log-concave distributions24
A framework of regularized low-rank matrix models for regression and classification21
Model-based clustering of multiple networks with a hierarchical algorithm20
Scalable methods for computing sharp extreme event probabilities in infinite-dimensional stochastic systems17
Optimal designs for nonlinear mixed-effects models using competitive swarm optimizer with mutated agents16
Sparse and geometry-aware generalisation of the mutual information for joint discriminative clustering and feature selection16
A limit formula and recursive algorithm for multivariate Normal tail probability16
Automatic search intervals for the smoothing parameter in penalized splines15
State-dependent importance sampling for estimating expectations of functionals of sums of independent random variables14
Joint latent space models for ranking data and social network14
Fast Bayesian inversion for high dimensional inverse problems14
Unbalanced distributed estimation and inference for the precision matrix in Gaussian graphical models13
Robust supervised learning with coordinate gradient descent12
Model-based clustering with missing not at random data12
Quantile-distribution functions and their use for classification, with application to naïve Bayes classifiers11
On predictive inference for intractable models via approximate Bayesian computation11
Latent structure blockmodels for Bayesian spectral graph clustering11
A multivariate heavy-tailed integer-valued GARCH process with EM algorithm-based inference11
Screen then select: a strategy for correlated predictors in high-dimensional quantile regression11
Parallelized integrated nested Laplace approximations for fast Bayesian inference11
Probabilistic time integration for semi-explicit PDAEs10
Hyperparameter optimization for randomized algorithms: a case study on random features10
Optimal designs for generalized linear mixed models based on the penalized quasi-likelihood method10
Variable selection using a smooth information criterion for distributional regression models10
Subgraph nomination: query by example subgraph retrieval in networks9
Computing marginal likelihoods via the Fourier integral theorem and pointwise estimation of posterior densities9
Extended fiducial inference for individual treatment effects via deep neural networks9
The clustered Mallows model9
Multivariate zero-inflated INGARCH models: Bayesian inference and composite likelihood approach9
On Bayesian wavelet shrinkage estimation of nonparametric regression models with stationary correlated noise9
Particle gradient descent model for point process generation9
Maximum softly-penalized likelihood for mixed effects logistic regression9
A novel approach for parameter estimation of mixture of two Weibull distributions in failure data modeling9
Classifier-dependent feature selection via greedy methods8
A generalized likelihood-based Bayesian approach for scalable joint regression and covariance selection in high dimensions8
Bayesian learning via neural Schrödinger–Föllmer flows8
Supervised learning via ensembles of diverse functional representations: the functional voting classifier8
Efficient importance sampling for large sums of independent and identically distributed random variables8
A data-adaptive method for outlier detection from functional data8
An efficient workflow for modelling high-dimensional spatial extremes8
Testing common degree-correction parameters of multilayer networks7
Variational Tobit Gaussian Process Regression7
Multi-index antithetic stochastic gradient algorithm7
Wasserstein principal component analysis for circular measures7
Semiparametric efficient estimation of genetic relatedness with machine learning methods7
An analysis of the modality and flexibility of the inverse stereographic normal distribution7
Nonparametric Bayesian online change point detection using kernel density estimation with nonparametric hazard function7
Improving power by conditioning on less in post-selection inference for changepoints7
A data-driven and model-based accelerated Hamiltonian Monte Carlo method for Bayesian elliptic inverse problems7
Bayesian design for sampling anomalous spatio-temporal data7
Structure-based hyperparameter selection with Bayesian optimization in multidimensional scaling7
Logit unfolding choice models for binary data7
Erlang mixture modeling for Poisson process intensities7
Fast Bayesian inference of block Nearest Neighbor Gaussian models for large data7
Penalized principal component analysis using smoothing7
Poisson subsampling-based estimation for growing-dimensional expectile regression in massive data6
INLA$$^+$$: approximate Bayesian inference for non-sparse models using HPC6
Functional concurrent hidden Markov model6
Improving tree probability estimation with stochastic optimization and variance reduction6
Topology-driven goodness-of-fit tests in arbitrary dimensions6
Penalized Cox’s proportional hazards model for high-dimensional survival data with grouped predictors6
Optimization of the generalized covariance estimator in noncausal processes6
A new flexible Bayesian hypothesis test for multivariate data6
Transformation models with informative partly interval-censored data6
A generalized expectation model selection algorithm for latent variable selection in multidimensional item response theory models6
A two-stage approach for Bayesian joint models: reducing complexity while maintaining accuracy6
Efficient simulation of p-tempered $$\alpha $$-stable OU processes6
Tests for simultaneous ordered alternatives in a two-way ANOVA with interaction6
Fused lasso nearly-isotonic signal approximation in general dimensions6
Multilevel latent class models for cross-classified categorical data: model definition and estimation through stochastic EM6
Persistent Sampling: Enhancing the Efficiency of Sequential Monte Carlo5
Asymptotic post-selection inference for regularized graphical models5
Graph-based algorithms for phase-type distributions5
A Joint estimation approach to sparse additive ordinary differential equations5
Limit theory and robust evaluation methods for the extremal properties of GARCH(p, q) processes5
Huber-energy measure quantization5
The stochastic proximal distance algorithm5
GP-ETAS: semiparametric Bayesian inference for the spatio-temporal epidemic type aftershock sequence model5
A Neural Network Integrated Accelerated Failure Time-Based Mixture Cure Model5
Maximum likelihood estimation of the Weibull distribution with reduced bias5
Network-assisted Semi-supervised Logistic Regression5
On the f-divergences between densities of a multivariate location or scale family5
Using prior-data conflict to tune Bayesian regularized regression models5
On the application of Gaussian graphical models to paired data problems5
Uniform calibration tests for forecasting systems with small lead time5
Correction to: The COR criterion for optimal subset selection in distributed estimation5
Mixture cure semiparametric additive hazard models under partly interval censoring — a penalized likelihood approach5
Adaptive random neighbourhood informed Markov chain Monte Carlo for high-dimensional Bayesian variable selection5
One-step closed-form estimator for generalized linear model with categorical explanatory variables5
Bias-enhanced support detection and root finding approach5
The forward–backward envelope for sampling with the overdamped Langevin algorithm5
Wavelet-based robust estimation and variable selection in nonparametric additive models5
Bayesian parameter inference for partially observed stochastic differential equations driven by fractional Brownian motion5
The effect of intrinsic dimension on the Bayes-error of projected quadratic discriminant classification5
Comparing unconstrained parametrization methods for return covariance matrix prediction5
Quantile regression feature selection and estimation with grouped variables using Huber approximation4
Exact computation of angular halfspace depth4
The Deep Latent Position Block Model for Block Clustering and Latent Representation of Nodes in Networks4
Limitations of the Wasserstein MDE for univariate data4
Nonconvex Dantzig selector and its parallel computing algorithm4
Estimation of ratios of normalizing constants using stochastic approximation: the SARIS algorithm4
Correction to : Variational inference and sparsity in high-dimensional deep Gaussian mixture models4
Fitting double hierarchical models with the integrated nested Laplace approximation4
Dynamic and robust Bayesian graphical models4
Large-scale constrained Gaussian processes for shape-restricted function estimation4
Total effects with constrained features4
Variance reduction for Metropolis–Hastings samplers4
Automatically adapting the number of state particles in SMC$$^2$$4
Simulation based composite likelihood4
Laplace based Bayesian inference for ordinary differential equation models using regularized artificial neural networks4
Consistent causal inference from time series with PC algorithm and its time-aware extension4
Support vector machine in big data: smoothing strategy and adaptive distributed inference4
Estimation and model selection for finite mixtures of Tukey’s g- &-h distributions4
Automatic Zig-Zag sampling in practice4
Spectral clustering on aggregated multilayer networks with covariates4
An expectile computation cookbook4
Gradient boosting for generalised additive mixed models4
Variable selection using conditional AIC for linear mixed models with data-driven transformations4
Modularized Bayesian analyses and cutting feedback in likelihood-free inference4
Affine-mapping based variational ensemble Kalman filter4
New forest-based approaches for sufficient dimension reduction4
PCA-uCPD: an ensemble method for multiple change-point detection in moderately high-dimensional data4
A fast look-up method for Bayesian mean-parameterised Conway–Maxwell–Poisson regression models4
funBIalign: a hierachical algorithm for functional motif discovery based on mean squared residue scores4
A test for the absence of aliasing or white noise in two-dimensional locally stationary wavelet processes4
Randomized self-updating process for clustering large-scale data4
Independence test via mutual information in the presence of measurement errors4
Constrained parsimonious model-based clustering4
Penalized empirical likelihood estimation and EM algorithms for closed-population capture–recapture models4
Efficient reduced-rank methods for Gaussian processes with eigenfunction expansions4
Deep neural networks for variable selection of higher-order nonparametric spatial autoregressive model4
Data-adaptive structural change-point detection via isolation4
Fitting Matérn smoothness parameters using automatic differentiation4
A fast epigraph and hypograph-based approach for clustering functional data4
COMBSS: best subset selection via continuous optimization4
Shrinkage for extreme partial least-squares4
Inference issue in multiscale geographically and temporally weighted regression4
Discriminative clustering with representation learning with any ratio of labeled to unlabeled data4
Systemic infinitesimal over-dispersion on graphical dynamic models4
Natural gradient hybrid variational inference with application to deep mixed models4
Sequential changepoint detection in neural networks with checkpoints4
Accelerated gradient methods for sparse statistical learning with nonconvex penalties4
Sparse estimation and inference for prediction-powered semi-supervised linear regression4
Multilevel importance sampling for rare events associated with the McKean–Vlasov equation4
Cauchy Markov random field priors for Bayesian inversion4
Geometry-informed irreversible perturbations for accelerated convergence of Langevin dynamics4
Inference of multivariate exponential Hawkes processes with inhibition and application to neuronal activity4
A fast and accurate numerical method for the left tail of sums of independent random variables4
Core-elements for large-scale least squares estimation3
Local Polynomial $$L_p$$-norm Regression3
Variational inference with vine copulas: an efficient approach for Bayesian computer model calibration3
Clustering longitudinal ordinal data via finite mixture of matrix-variate distributions3
Unlabelled landmark matching via Bayesian data selection, and application to cell matching across imaging modalities3
Fast Gibbs sampling for the local-seasonal-global trend Bayesian exponential smoothing model3
Robust and efficient sparse learning over networks: a decentralized surrogate composite quantile regression approach3
Sequential model identification with reversible jump ensemble data assimilation method3
Feature splitting parallel algorithm for Dantzig selectors3
Co-clustering of evolving count matrices with the dynamic latent block model: application to pharmacovigilance3
The computational asymptotics of Gaussian variational inference and the Laplace approximation3
Structured prior distributions for the covariance matrix in latent factor models3
Tree-based variational inference for Poisson log-normal models3
Augmented pseudo-marginal Metropolis–Hastings for partially observed diffusion processes3
Shape modeling with spline partitions3
On simulation of continuous determinantal point processes3
Bayesian projection pursuit regression3
Functional mixtures-of-experts3
Greedy recursive spectral bisection for modularity-bound hierarchical divisive community detection3
Sequential Bayesian Registration for Functional Data3
Graph matching beyond perfectly-overlapping Erdős–Rényi random graphs3
High-dimensional order-free multivariate spatial disease mapping3
Identifying Collapsible Sets in Directed Graphical Models via Inducing Paths3
Unbiased and multilevel methods for a class of diffusions partially observed via marked point processes3
Sparse estimation in high-dimensional linear errors-in-variables regression via a covariate relaxation method3
A sparse matrix formulation of model-based ensemble Kalman filter3
A sparse PAC-Bayesian approach for high-dimensional quantile prediction3
Optimal scaling of random walk Metropolis algorithms using Bayesian large-sample asymptotics3
An EM algorithm for fitting matrix-variate normal distributions on interval-censored and missing data3
Frugal Gaussian clustering of huge imbalanced datasets through a bin-marginal approach3
Detection of spatiotemporal changepoints: a generalised additive model approach3
Anytime parallel tempering3
Geographically weighted quantile regression for count Data3
Density regression via Dirichlet process mixtures of normal structured additive regression models3
An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization3
Improving the prediction accuracy of statistical models: A new hierarchical clustering approach3
Statistical inference and goodness-of-fit test in functional data via error distribution function3
Efficient estimation of expected information gain in Bayesian experimental design with multi-index Monte Carlo3
Efficient Shapley performance attribution for least-squares regression3
Correction: PCA-uCPD: an ensemble method for multiple change-point detection in moderately high-dimensional data3
Bayesian tree-based heterogeneous mediation analysis with a time-to-event outcome3
High-dimensional structure learning of sparse vector autoregressive models using fractional marginal pseudo-likelihood3
Online Bayesian changepoint detection for network Poisson processes with community structure3
The recursive variational Gaussian approximation (R-VGA)3
Taming numerical imprecision by adapting the KL divergence to negative probabilities3
Novel sampling method for the von Mises–Fisher distribution3
Bootstrap estimation of the proportion of outliers in robust regression3
Double-loop importance sampling for McKean–Vlasov stochastic differential equation3
Individualized causal mediation analysis with continuous treatment using conditional generative adversarial networks2
Online structural break detection in financial durations2
Expectile and M-quantile regression for panel data2
Distributed Estimation and Inference for High-Dimensional Confounded Models2
Efficient modeling of quasi-periodic data with seasonal Gaussian process2
Two-armed Bandit Bootstrap for Model-free Equivalent Rank Test2
IDGM: an approach to estimate the graphical model of interval-valued data2
False discovery rate envelopes2
A numerically stable algorithm for integrating Bayesian models using Markov melding2
An improved bisection-type algorithm for control chart calibration2
Generalized linear models for massive data via doubly-sketching2
Subsampling approach for least squares fitting of semi-parametric accelerated failure time models to massive survival data2
Summary statistics and discrepancy measures for approximate Bayesian computation via surrogate posteriors2
Split Hamiltonian Monte Carlo revisited2
Fuzzy clustering with Barber modularity regularization2
Multilevel estimation of normalization constants using ensemble Kalman–Bucy filters2
Estimating Expectile-Optimal Treatment Regimes2
Insufficient Gibbs sampling2
Density deconvolution under a k-monotonicity constraint2
Functional autoencoder for smoothing and representation learning2
Estimating the number of true null hypotheses based on change point of observed p values2
Fast and universal estimation of latent variable models using extended variational approximations2
A constant-per-iteration likelihood ratio test for online changepoint detection for exponential family models2
Nonparametric empirical bayes prediction in mixed models2
Parallel ADMM Algorithm with Gaussian Back Substitution for High-Dimensional Quantile Regression and Classification2
Information-Theoretic Criteria for Optimizing Designs of Individually Randomized Stepped-Wedge Clinical Trials2
Explainable generalized additive neural networks with independent neural network training2
Individualized treatment rules based on adaptive transfer-dragonnet2
The second–derivative lower–bound function (SeLF) algorithm and three acceleration techniques for maximization with strongly stable convergence2
Efficient and generalizable tuning strategies for stochastic gradient MCMC2
Estimation of a likelihood ratio ordered family of distributions2
Adaptive online variance estimation in particle filters: the ALVar estimator2
A comparison of likelihood-free methods with and without summary statistics2
High-dimensional regression with potential prior information on variable importance2
Trans-cGAN: transformer-Unet-based generative adversarial networks for cross-modality magnetic resonance image synthesis2
Online prediction of extreme conditional quantiles via B-spline interpolation2
Learning binary undirected graph in low dimensional regime2
Penalized quadratic inference functions estimation for fixed effects partially linear single index spatial error model2
Generalized spherical principal component analysis2
Mixture of multivariate Gaussian processes for classification of irregularly sampled satellite image time-series2
Quantile ratio regression2
Lévy Langevin Monte Carlo2
S-SIRUS: an explainability algorithm for spatial regression Random Forest2
Performance analysis of greedy algorithms for minimising a Maximum Mean Discrepancy2
General Jackknife empirical likelihood and its applications2
Double debiased estimation and inference for longitudinal generalized linear models with hidden confounders2
A Bayesian parametrized method for interval-valued regression models2
Group sparse structural smoothing recovery: model, statistical properties and algorithm2
Graphical test for discrete uniformity and its applications in goodness-of-fit evaluation and multiple sample comparison2
On proportional volume sampling for experimental design in general spaces2
Scalable computations for nonstationary Gaussian processes2
$$\pi $$VAE: a stochastic process prior for Bayesian deep learning with MCMC2
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