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Content
2023, Volume 110, Issue 2
- 283-299 On boosting the power of Chatterjee’s rank correlation
by Z Lin & F Han - 301-318 Hug and hop: a discrete-time, nonreversible Markov chain Monte Carlo algorithm
by M Ludkin & C Sherlock - 319-337 Gaussian universal likelihood ratio testing
by Robin Dunn & Aaditya Ramdas & Sivaraman Balakrishnan & Larry Wasserman - 339-360 Gradient-based sparse principal component analysis with extensions to online learning
by Yixuan Qiu & Jing Lei & Kathryn Roeder - 361-379 Additive models for symmetric positive-definite matrices and Lie groups
by Z Lin & H -G Müller & B U Park - 381-393 Functional linear regression for discretely observed data: from ideal to reality
by Hang Zhou & Fang Yao & Huiming Zhang - 395-410 Multi-stage optimal dynamic treatment regimes for survival outcomes with dependent censoring
by Hunyong Cho & Shannon T Holloway & David J Couper & Michael R Kosorok - 411-430 Kernel two-sample tests in high dimensions: interplay between moment discrepancy and dimension-and-sample orders
by Jian Yan & Xianyang Zhang - 431-447 Lasso-adjusted treatment effect estimation under covariate-adaptive randomization
by Hanzhong Liu & Fuyi Tu & Wei Ma - 449-465 Evaluating causes of effects by posterior effects of causes
by Zitong Lu & Zhi Geng & Wei Li & Shengyu Zhu & Jinzhu Jia - 467-483 Design-based theory for cluster rerandomization
by Xin Lu & Tianle Liu & Hanzhong Liu & Peng Ding - 485-498 Sample-constrained partial identification with application to selection bias
by Matthew J Tudball & Rachael A Hughes & Kate Tilling & Jack Bowden & Qingyuan Zhao - 499-518 Bootstrapping Whittle estimators
by J -P Kreiss & E Paparoditis - 519-536 A multiplicative structural nested mean model for zero-inflated outcomes
by Miao Yu & Wenbin Lu & Shu Yang & Pulak Ghosh - 537-549 Optimal row-column designs
by Zheng Zhou & Yongdao Zhou - 551-558 Clustering consistency with Dirichlet process mixtures
by F Ascolani & A Lijoi & G Rebaudo & G Zanella
2023, Volume 110, Issue 1
- 1-13 Propensity scores in the design of observational studies for causal effects
by P R Rosenbaum & D B Rubin - 15-32 Subsampling sparse graphons under minimal assumptions
by Robert Lunde & Purnamrita Sarkar - 33-50 Localized conformal prediction: a generalized inference framework for conformal prediction
by Leying Guan - 51-68 Uniform inference in high-dimensional Gaussian graphical models
by S Klaassen & J Kueck & M Spindler & V Chernozhukov - 69-81 On F-modelling-based empirical Bayes estimation of variances
by Yeil Kwon & Zhigen Zhao - 83-99 Testing generalized linear models with high-dimensional nuisance parameters
by Jinsong Chen & Quefeng Li & Hua Yun Chen - 119-134 Data integration: exploiting ratios of parameter estimates from a reduced external model
by Jeremy M G Taylor & Kyuseong Choi & Peisong Han - 135-153 Spherical clustering in detection of groups of concomitant extremes
by V Fomichov & J Ivanovs - 155-168 Minimax designs for causal effects in temporal experiments with treatment habituation
by Guillaume W Basse & Yi Ding & Panos Toulis - 169-185 Robust differential abundance test in compositional data
by Shulei Wang - 187-203 Linearized maximum rank correlation estimation
by Guohao Shen & Kani Chen & Jian Huang & Yuanyuan Lin - 205-223 Response best-subset selector for multivariate regression with high-dimensional response variables
by Jianhua Hu & Jian Huang & Xiaoqian Liu & Xu Liu - 225-247 Separable expansions for covariance estimation via the partial inner product
by T Masak & S Sarkar & V M Panaretos - 249-256 Seeded binary segmentation: a general methodology for fast and optimal changepoint detection
by S Kovács & P Bühlmann & H Li & A Munk - 257-264 A simple and general debiased machine learning theorem with finite-sample guarantees
by V Chernozhukov & W K Newey & R Singh - 265-272 Regression of exchangeable relational arrays
by F W Marrs & B K Fosdick & T H Mccormick - 273-280 Optimal minimax random designs for weighted least squares estimators
by D Azriel
2022, Volume 109, Issue 4
- 881-900 Mean decrease accuracy for random forests: inconsistency, and a practical solution via the Sobol-MDA
[Explaining individual predictions when features are dependent: more accurate approximations to Shapley values]
by Clément Bénard & Sébastien Da Veiga & Erwan Scornet - 901-919 Scalable and accurate variational Bayes for high-dimensional binary regression models
[Bayesian analysis of binary and polychotomous response data]
by Augusto Fasano & Daniele Durante & Giacomo Zanella - 921-935 Particle filter efficiency under limited communication
[Distributed stochastic gradient MCMC]
by Deborshee Sen - 937-955 A global stochastic optimization particle filter algorithm
[Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization]
by M Gerber & R Douc - 957-974 Distribution-on-distribution regression via optimal transport maps
[Upper and lower risk bounds for estimating the Wasserstein barycenter of random measures on the real line]
by Laya Ghodrati & Victor M Panaretos - 975-992 Fréchet sufficient dimension reduction for random objects
[Some asymptotic theory for the bootstrap]
by Chao Ying & Zhou Yu - 993-1014 Graphical Gaussian process models for highly multivariate spatial data
[Cross-covariance functions for multivariate random fields based on latent dimensions]
by Debangan Dey & Abhirup Datta & Sudipto Banerjee - 1015-1031 Efficient semiparametric estimation of network treatment effects under partial interference
[Multivariate binary discrimination by the kernel method]
by C Park & H Kang - 1033-1046 High-dimensional linear regression via implicit regularization
[Simultaneous analysis of lasso and Dantzig selector]
by Peng Zhao & Yun Yang & Qiao-Chu He - 1047-1066 A proximal distance algorithm for likelihood-based sparse covariance estimation
[Estimating large correlation matrices for international migration]
by Jason Xu & Kenneth Lange - 1067-1083 Significance testing for canonical correlation analysis in high dimensions
[Inconsistency of the bootstrap when a parameter is on the boundary of the parameter space]
by Ian W McKeague & Xin Zhang - 1085-1100 Decomposition, identification and multiply robust estimation of natural mediation effects with multiple mediators
[Generalized causal mediation analysis]
by Fan Xia & Kwun Chuen Gary Chan - 1101-1116 Sensitivity analysis for unmeasured confounding in the estimation of marginal causal effects
[Doubly robust estimation in missing data and causal inference models]
by I Ciocănea-Teodorescu & E E Gabriel & A Sjölander - 1117-1132 An approximate randomization test for the high-dimensional two-sample Behrens–Fisher problem under arbitrary covariances
[Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays]
by Rui Wang & Wangli Xu - 1133-1148 Functional hybrid factor regression model for handling heterogeneity in imaging studies
[Relationships between years of education and gray matter volume, metabolism and functional connectivity in healthy elders]
by C Huang & H Zhu - 1149-1155 Adjusting the Benjamini–Hochberg method for controlling the false discovery rate in knockoff-assisted variable selection
[Controlling the false discovery rate via knockoffs]
by Sanat K Sarkar & Cheng Yong Tang - 1157-1164 Is the mode elicitable relative to unimodal distributions?
[Inflation report: August 2019. Monetary Policy Committee, Bank of England, London]
by Claudio Heinrich-Mertsching & Tobias Fissler - 1165-1172 Average direct and indirect causal effects under interference
[Estimating average causal effects under general interference, with application to a social network experiment]
by Yuchen Hu & Shuangning Li & Stefan Wager - 1173-1180 A correlation-shrinkage prior for Bayesian prediction of the two-dimensional Wishart model
[Modeling covariance matrices in terms of standard deviations and correlations, with application to shrinkage]
by T Sei & F Komaki - 1181-1182 Correction to: ‘Valid sequential inference on probability forecast performance’
[Valid sequential inference on probability forecast performance]
by Alexander Henzi & Johanna F Ziegel
2022, Volume 109, Issue 3
- 569-587 Multi-scale Fisher’s independence test for multivariate dependence
[A simple measure of conditional dependence]
by S Gorsky & L Ma - 589-592 Discussion of ‘Multi-scale Fisher’s independence test for multivariate dependence’
[Adaptive test of independence based on HSIC measures]
by T B Berrett - 593-596 Discussion of ‘Multi-scale Fisher’s independence test for multivariate dependence’
[Multi-scale Fisher’s independence test for multivariate dependence]
by D Lee & H El-Zaatari & M R Kosorok & X Li & K Zhang - 597-603 Discussion of ‘Multi-scale Fisher’s independence test for multivariate dependence’
[Adaptive test of independence based on HSIC measures]
by A Schrab & W Jitkrittum & Z Szabó & D Sejdinovic & A Gretton - 605-609 Rejoinder: ‘Multi-scale Fisher’s independence test for multivariate dependence’
[Discussion of ‘Multi-scale Fisher’s independence test for multivariate dependence’]
by S Gorsky & L Ma - 611-629 Searching for robust associations with a multi-environment knockoff filter
[A global reference for human genetic variation]
by S Li & M Sesia & Y Romano & E Candès & C Sabatti - 631-645 A high-dimensional power analysis of the conditional randomization test and knockoffs
[On the construction of knockoffs in case-control studies]
by Wenshuo Wang & Lucas Janson - 647-663 Valid sequential inference on probability forecast performance
[A comparison of the ECMWF, MSC, and NCEP global ensemble prediction systems]
by Alexander Henzi & Johanna F Ziegel - 665-681 Partial separability and functional graphical models for multivariate Gaussian processes
[Tests for separability in nonparametric covariance operators of random surfaces]
by J Zapata & S Y Oh & A Petersen - 683-706 Latent space models for multiplex networks with shared structure
[Inference for multiple heterogeneous networks with a common invariant subspace]
by P W MacDonald & E Levina & J Zhu - 707-720 Joint latent space models for network data with high-dimensional node variables
[Statistical inference on random dot product graphs: a survey]
by Xuefei Zhang & Gongjun Xu & Ji Zhu - 721-734 Local linear graphon estimation using covariates
[Representations for partially exchangeable arrays of random variables]
by S Chandna & S C Olhede & P J Wolfe - 735-750 Lugsail lag windows for estimating time-average covariance matrices
[Exact expected values of variance estimators for simulation]
by D Vats & J M Flegal - 751-768 Risk bounds for quantile trend filtering
[-penalized quantile regression in high-dimensional sparse models]
by Oscar Hernan Madrid Padilla & Sabyasachi Chatterjee - 769-782 Determining the number of factors in high-dimensional generalized latent factor models
[Eigenvalue ratio test for the number of factors]
by Y Chen & X Li - 783-798 Asymptotic distribution-free changepoint detection for data with repeated observations
[Graph-based change-point detection]
by Hoseung Song & Hao Chen - 799-815 Regression-based causal inference with factorial experiments: estimands, model specifications and design-based properties
[Are Emily and Greg more employable than Lakisha and Jamal? A field experiment on labor market discrimination]
by Anqi Zhao & Peng Ding - 817-835 Generalized infinite factorization models
[A latent factor linear mixed model for high-dimensional longitudinal data analysis]
by L Schiavon & A Canale & D B Dunson - 837-851 Wavelet spectra for multivariate point processes
[The spectral analysis of point processes]
by E A K Cohen & A J Gibberd - 853-864 Uniqueness and global optimality of the maximum likelihood estimator for the generalized extreme value distribution
[Reference analysis]
by Likun Zhang & Benjamin A Shaby - 865-872 Heterogeneous coefficients, control variables and identification of multiple treatment effects
[Multivalued treatments and decomposition analysis: An application to the WIA program]
by W K Newey & S Stouli - 873-880 On the relative efficiency of the intent-to-treat Wilcoxon–Mann–Whitney test in the presence of noncompliance
[Instrumental variables estimates of the effect of subsidized training on the quantiles of trainee earnings]
by Lu Mao
2022, Volume 109, Issue 2
- 277-293 Fast and powerful conditional randomization testing via distillation
[Controlling the false discovery rate via knockoffs]
by Molei Liu & Eugene Katsevich & Lucas Janson & Aaditya Ramdas - 295-315 Confidence regions in Wasserstein distributionally robust estimation
[Distributionally robust groupwise regularization estimator]
by Jose Blanchet & Karthyek Murthy & Nian Si - 317-333 On the power of Chatterjee’s rank correlation
[Adaptive test of independence based on HSIC measures]
by H Shi & M Drton & F Han - 335-349 A discrete bouncy particle sampler
[Hypocoercivity of piecewise deterministic Markov process-Monte Carlo]
by C Sherlock & A H Thiery - 351-367 Semi-exact control functionals from Sard’s method
[Zero-variance principle for Monte Carlo algorithms]
by L F South & T Karvonen & C Nemeth & M Girolami & C J Oates - 369-385 Efficient Bernoulli factory Markov chain Monte Carlo for intractable posteriors
[Optimal scaling of MCMC beyond Metropolis]
by D Vats & F B Gonçalves & K Łatuszyński & G O Roberts - 387-403 High-dimensional semi-supervised learning: in search of optimal inference of the mean
[Multivariate tests comparing binomial probabilities, with application to safety studies for drugs]
by Yuqian Zhang & Jelena Bradic - 405-420 High-dimensional log-error-in-variable regression with applications to microbial compositional data analysis
[Log contrast models for experiments with mixtures]
by Pixu Shi & Yuchen Zhou & Anru R Zhang - 421-438 Estimation of genetic correlation with summary association statistics
[A global reference for human genetic variation]
by Jianqiao Wang & Hongzhe Li - 439-455 Scalar-on-function local linear regression and beyond
[Cross-validated estimations in the single-functional index model]
by F Ferraty & S NAGY - 457-471 Smoothed nested testing on directed acyclic graphs
[Controlling the false discovery rate via knockoffs]
by J H Loper & L Lei & W Fithian & W Tansey - 473-487 Inverse moment methods for sufficient forecasting using high-dimensional predictors
[Eigenvalue ratio test for the number of factors]
by Wei Luo & Lingzhou Xue & Jiawei Yao & Xiufan Yu - 489-501 A minimum aberration-type criterion for selecting space-filling designs
[Optimal sliced Latin hypercube designs]
by Ye Tian & Hongquan Xu - 503-519 Estimation under matrix quadratic loss and matrix superharmonicity
[Shrinkage estimation with a matrix loss function]
by T Matsuda & W E Strawderman - 521-534 Asymptotics of sample tail autocorrelations for tail-dependent time series: phase transition and visualization
[Tail dependence and indicators of systemic risk for large US depositories]
by Ting Zhang - 535-541 Inverses of Matérn covariances on grids
[Spatial modeling with R-INLA: A review]
by Joseph Guinness - 543-550 Testing for unit roots based on sample autocovariances
[Heteroskedasticity and autocorrelation consistent covariance matrix estimation]
by Jinyuan Chang & Guanghui Cheng & Qiwei Yao - 551-558 On the inconsistency of matching without replacement
[Large sample properties of matching estimators for average treatment effects]
by F Sävje - 559-566 Multiplicative effect modelling: the general case
[Update of Dutch multicenter dose-escalation trial of radiotherapy for localized prostate cancer]
by J Yin & S Markes & T S Richardson & L Wang
2022, Volume 109, Issue 1
- 1-16 Optimal post-selection inference for sparse signals: a nonparametric empirical Bayes approach
[Controlling the false discovery rate: A practical and powerful approach to multiple testing]
by S Woody & O H M Padilla & J G Scott - 17-32 More for less: predicting and maximizing genomic variant discovery via Bayesian nonparametrics
[A global reference for human genetic variation]
by Lorenzo Masoero & Federico Camerlenghi & Stefano Favaro & Tamara Broderick - 33-47 Inference on the average treatment effect under minimization and other covariate-adaptive randomization methods
[Optimum biased coin designs for sequential clinical trials with prognostic factors]
by Ting Ye & Yanyao Yi & Jun Shao - 49-65 Efficient adjustment sets in causal graphical models with hidden variables
[Double/debiased machine learning for treatment and structural parameters]
by E Smucler & F Sapienza & A Rotnitzky - 67-83 Heterogeneity-aware and communication-efficient distributed statistical inference
[Privacy, confidentiality, and electronic medical records]
by Rui Duan & Yang Ning & Yong Chen - 85-102 Dimension reduction for covariates in network data
[On semidefinite relaxations for the block model]
by Junlong Zhao & Xiumin Liu & Hansheng Wang & Chenlei Leng - 103-122 Integrated conditional moment test and beyond: when the number of covariates is divergent
[Using crowd-source based features from social media and conventional features to predict the movies popularity]
by Falong Tan & Lixing Zhu - 123-136 Large-scale model selection in misspecified generalized linear models
[Information theory and an extension of the maximum likelihood principle]
by Emre Demirkaya & Yang Feng & Pallavi Basu & Jinchi Lv - 137-152 Backfitting tests in generalized structured models
[Effect measures in non-parametric regression with interactions between continuous exposures]
by E Mammen & S Sperlich - 153-164 General ways to improve false coverage rate-adjusted selective confidence intervals
[False discovery rate-adjusted multiple confidence intervals for selected parameters]
by Haibing Zhao - 165-179 Interpoint-ranking sign covariance for the test of independence
[Prediction by supervised principal components]
by Haeun Moon & Kehui Chen - 181-194 Stratification and optimal resampling for sequential Monte Carlo
[Posterior Cramér-Rao bounds for sequential estimation]
by Yichao Li & Wenshuo Wang & K E Deng & Jun S Liu - 195-208 Statistical inference on shape and size indexes for counting processes
[Rank estimation of a transformation model with observed truncation]
by Yifei Sun & Sy Han Chiou & Kieren A Marr & Chiung-Yu Huang - 209-226 Sparse functional linear discriminant analysis
[On the use of reproducing kernel Hilbert spaces in functional classification]
by Juhyun Park & Jeongyoun Ahn & Yongho Jeon - 227-241 Missing at random: a stochastic process perspective
[Contribution to the discussion of ‘Longitudinal data with dropout: Objectives, assumptions and a proposal’ by P. J. Diggle, D. Farewell and R. Henderson]
by D M Farewell & R M Daniel & S R Seaman - 243-256 Estimation of the cure rate for distributions in the Gumbel maximum domain of attraction under insufficient follow-up
[Cure models in survival analysis]
by Mikael Escobar-Bach & Ross Maller & Ingrid Van Keilegom & Muzhi Zhao - 257-264 Distributed inference for the extreme value index
[Statistics of heteroscedastic extremes]
by Liujun Chen & Deyuan Li & Chen Zhou - 265-272 Identifiability of causal effects with multiple causes and a binary outcome
[Statistical inference in factor analysis]
by Dehan Kong & Shu Yang & Linbo Wang - 273-273 Correction to: ‘On semiparametric modelling, estimation and inference for survival data subject to dependent censoring’
by N W Deresa & I Van Keilegom - 275-275 Correction to: ‘Approximating posteriors with high-dimensional nuisance parameters via integrated rotated Gaussian approximation’
by W van den Boom & G Reeves & D B Dunson
2021, Volume 108, Issue 4
- 757-773 Event history and topological data analysis
[Persistence images: a stable vector representation of persistent homology]
by K Garside & A Gjoka & R Henderson & H Johnson & I Makarenko - 775-778 Discussion of ‘Event history and topological data analysis’
[Persistence images: A stable vector representation of persistent homology]
by Moo K Chung & Hernando Ombao - 779-783 Discussion of ‘Event history and topological data analysis’
[A cautionary example of the use of second-order methods for analysing point patterns]
by C A N Biscio & J Møller - 785-788 Discussion of ‘Event history and topological data analysis’
[Event history and topological data analysis]
by Peter Bubenik - 789-793 Rejoinder: ‘Event history and topological data analysis’
[Discussion of ‘Event history and topological data analysis]
by K Garside & A Gjoka & R Henderson & H Johnson & I Makarenko - 795-814 Consistency guarantees for greedy permutation-based causal inference algorithms
[Ordering-based causal structure learning in the presence of latent variables]
by L Solus & Y Wang & C Uhler - 815-828 Regression adjustment in completely randomized experiments with a diverging number of covariates
[Covariance adjustments for the analysis of randomized field experiments]
by Lihua Lei & Peng Ding - 829-843 Changepoint inference in the presence of missing covariates for principal surrogate evaluation in vaccine trials
[On the existence of maximum likelihood estimates in logistic regression models]
by Tao Yang & Ying Huang & Youyi Fong - 845-855 A method of constructing maximin distance designs
[Interleaved lattice-based maximin distance designs]
by Wenlong Li & Min-Qian Liu & Boxin Tang - 857-879 Elicitation complexity of statistical properties
[A characterization of scoring rules for linear properties]
by Rafael M Frongillo & Ian A Kash - 881-894 Estimation of local treatment effects under the binary instrumental variable model
[Bootstrap tests for distributional treatment effects in instrumental variable models]
by Linbo Wang & Yuexia Zhang & Thomas S Richardson & James M Robins - 895-913 Bio-equivalence tests in functional data by maximum deviation
[On the prediction of stationary functional time series]
by Holger Dette & Kevin Kokot - 915-931 Covariate adaptive familywise error rate control for genome-wide association studies
[A global reference for human genetic variation]
by Huijuan Zhou & Xianyang Zhang & Jun Chen - 933-946 Learning block structures in U-statistic-based matrices
[Consistency of AIC and BIC in estimating the number of significant components in high-dimensional principal component analysis]
by Weiping Zhang & Baisuo Jin & Zhidong Bai - 947-963 Maximum likelihood estimation for semiparametric regression models with panel count data
[Cox’s regression model for counting processes: A large sample study]
by Donglin Zeng & D Y Lin - 965-979 On semiparametric modelling, estimation and inference for survival data subject to dependent censoring
[Identifiability of the multinormal and other distributions under competing risks model]
by N W Deresa & I Van Keilegom - 981-988 Bagging cross-validated bandwidths with application to big data
[baggedcv: Bagged cross-validation for kernel density bandwidth selection]
by D Barreiro-Ures & R Cao & M Francisco-Fernández & J D Hart - 989-995 Nontestability of instrument validity under continuous treatments
[Identification of causal effects using instrumental variables]
by F F Gunsilius - 997-1003 Admissible estimators of a multivariate normal mean vector when the scale is unknown
[A family of minimax estimators of the mean of a multivariate normal distribution]
by Y Maruyama & W E Strawderman
2021, Volume 108, Issue 3
- 535-539 Discussion of ‘Estimating time-varying causal excursion effects in mobile health with binary outcomes’
by Y Zhang & E B Laber - 541-550 Discussion of ‘Estimating time-varying causal excursion effects in mobile health with binary outcomes’
by F Richard Guo & Thomas S Richardson & James M Robins - 643-659 A parsimonious personalized dose-finding model via dimension reduction
by Wenzhuo Zhou & Ruoqing Zhu & Donglin Zeng
2021, Volume 108, Issue 2
- 253-267 A general interactive framework for false discovery rate control under structural constraints
[Controlling the false discovery rate via knockoffs]
by Lihua Lei & Aaditya Ramdas & William Fithian - 269-282 Approximating posteriors with high-dimensional nuisance parameters via integrated rotated Gaussian approximation
[The E2F family: Specific functions and overlapping interests]
by W van den Boom & G Reeves & D B Dunson - 283-297 Statistical properties of sketching algorithms
[The fast Johnson Lindenstrauss transform and approximate nearest neighbors]
by D C Ahfock & W J Astle & S Richardson - 299-319 Quasi-oracle estimation of heterogeneous treatment effects
[TensorFlow: A system for large-scale machine learning]
by X Nie & S Wager - 321-334 Inference for treatment effect parameters in potentially misspecified high-dimensional models
[Approximate residual balancing: Debiased inference of average treatment effects in high dimensions]
by Oliver Dukes & Stijn Vansteelandt - 335-351 Specification tests for covariance structures in high-dimensional statistical models
[Corrections to LRT on large-dimensional covariance matrix by RMT]
by X Guo & C Y Tang - 353-365 On the use of a penalized quasilikelihood information criterion for generalized linear mixed models
[A new look at the statistical model identification]
by Francis K C Hui - 367-379 Posterior contraction in sparse generalized linear models
[Model selection and minimax estimation in generalized linear models]
by Seonghyun Jeong & Subhashis Ghosal - 381-396 The uniform general signed rank test and its design sensitivity
[A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations]
by S R Howard & S D Pimentel - 397-412 An assumption-free exact test for fixed-design linear models with exchangeable errors
[Rank tests of sub-hypotheses in the general linear regression]
by Lihua Lei & Peter J Bickel - 413-424 On quadratic forms in multivariate generalized hyperbolic random vectors
[Expected shortfall: A natural coherent alternative to value at risk]
by Simon A Broda & Juan Arismendi Zambrano - 425-442 Estimating differential latent variable graphical models with applications to brain connectivity
[Machine learning for neuroimaging with scikit-learn]
by S Na & M Kolar & O Koyejo - 443-454 Lattice-based designs with quasi-optimal separation distance on all projections
[A framework for controlling sources of inaccuracy in Gaussian process emulation of deterministic computer experiments]
by Xu He - 455-468 Poisson reduced-rank models with an application to political text data
[Eigenvalue ratio test for the number of factors]
by Carsten Jentsch & Eun Ryung Lee & Enno Mammen - 469-489 Finite-time analysis of vector autoregressive models under linear restrictions
[Nested reduced-rank autogressive models for multiple time series]
by Yao Zheng & Guang Cheng - 491-506 Nonsmooth backfitting for the excess risk additive regression model with two survival time scales
[A linear regression model for the analysis of life times]
by M Hiabu & J P Nielsen & T H Scheike
2021, Volume 108, Issue 1
- 1-16 The asymptotic distribution of modularity in weighted signed networks
by Rong Ma & Ian Barnett - 17-36 Hypothesis testing for phylogenetic composition: a minimum-cost flow perspective
by Shulei Wang & T Tony Cai & Hongzhe Li - 37-51 Large-sample asymptotics of the pseudo-marginal method
by S M Schmon & G Deligiannidis & A Doucet & M K Pitt - 53-69 In search of lost mixing time: adaptive Markov chain Monte Carlo schemes for Bayesian variable selection with very large p
by J E Griffin & K G Łatuszyński & M F J Steel - 71-82 Jeffreys-prior penalty, finiteness and shrinkage in binomial-response generalized linear models
by Ioannis Kosmidis & David Firth - 83-97 Matrix-variate logistic regression with measurement error
by Junhan Fang & Grace Y Yi - 99-112 Optimal subsampling for quantile regression in big data
by Haiying Wang & Yanyuan Ma - 113-126 High-quantile regression for tail-dependent time series
by Ting Zhang - 127-147 High-dimensional empirical likelihood inference
by Jinyuan Chang & Song Xi Chen & Cheng Yong Tang & Tong Tong Wu - 149-166 An asymptotic and empirical smoothing parameters selection method for smoothing spline ANOVA models in large samples
by Xiaoxiao Sun & Wenxuan Zhong & Ping Ma - 167-181 Functional regression on the manifold with contamination
by Zhenhua Lin & Fang Yao - 183-198 Heterogeneous individual risk modelling of recurrent events
by Huijuan Ma & Limin Peng & Chiung-Yu Huang & Haoda Fu - 199-214 Modelling temporal biomarkers with semiparametric nonlinear dynamical systems
by Ming Sun & Donglin Zeng & Yuanjia Wang - 215-222 Jump or kink: on super-efficiency in segmented linear regression breakpoint estimation
by Yining Chen - 223-230 Event history analysis of dynamic networks
by T Sit & Z Ying & Y Yu - 231-238 Characterization of parameters with a mixed bias property
by A Rotnitzky & E Smucler & J M Robins - 239-246 Testing for measurement error in survey data analysis using paradata
by D N Da Silva & C J Skinner - 247-251 A likelihood analysis of quantile-matching transformations
by P McCullagh & M F Tresoldi
2020, Volume 107, Issue 3
- 513-532 Determining the dependence structure of multivariate extremes
by E S Simpson & J L Wadsworth & J A Tawn - 533-554 Robust estimation of causal effects via a high-dimensional covariate balancing propensity score
by Yang Ning & Peng Sida & Kosuke Imai - 555-572 A nonparametric approach to high-dimensional k-sample comparison problems
by Subhadeep Mukhopadhyay & Kaijun Wang - 573-589 Estimation and inference for the indirect effect in high-dimensional linear mediation models
by Ruixuan Rachel Zhou & Liewei Wang & Sihai Dave Zhao - 591-607 Empirical likelihood test for a large-dimensional mean vector
by Xia Cui & Runze Li & Guangren Yang & Wang Zhou - 609-625 Sparse semiparametric canonical correlation analysis for data of mixed types
by Grace Yoon & Raymond J Carroll & Irina Gaynanova - 627-646 Spatial blind source separation
by François Bachoc & Marc G Genton & Klaus Nordhausen & Anne Ruiz-Gazen & Joni Virta - 647-660 A robust method for shift detection in time series
by H Dehling & R Fried & M Wendler - 661-675 Generalized instrumental inequalities: testing the instrumental variable independence assumption
by Désiré Kédagni & Ismael Mourifié - 677-688 Adaptive critical value for constrained likelihood ratio testing
by Diaa Al Mohamad & Erik W Van Zwet & Eric Cator & Jelle J Goeman - 689-703 Generalized integration model for improved statistical inference by leveraging external summary data
by Han Zhang & Lu Deng & Mark Schiffman & Jing Qin & Kai Yu - 705-722 Path weights in concentration graphs
by Alberto Roverato & Robert Castelo - 723-735 More efficient approximation of smoothing splines via space-filling basis selection
by Cheng Meng & Xinlian Zhang & Jingyi Zhang & Wenxuan Zhong & Ping Ma - 737-744 A note on the accuracy of adaptive Gauss–Hermite quadrature
by Shaobo Jin & Björn Andersson - 745-752 Bayesian cumulative shrinkage for infinite factorizations
by Sirio Legramanti & Daniele Durante & David B Dunson - 753-760 Bootstrapping M-estimators in generalized autoregressive conditional heteroscedastic models
by K Mukherjee - 761-768 Fast closed testing for exchangeable local tests
by E Dobriban - 769-769 ‘Unbiased Hamiltonian Monte Carlo with couplings’
by J Heng & P E Jacob
2020, Volume 107, Issue 2
- 257-276 Network cross-validation by edge sampling
by Tianxi Li & Elizaveta Levina & Ji Zhu - 277-280 Discussion of ‘Network cross-validation by edge sampling’
by Jinyuan Chang & Eric D Kolaczyk & Qiwei Yao - 281-284 Discussion of ‘Network cross-validation by edge sampling’
by Chao Gao & Zongming Ma - 285-287 Discussion of ‘Network cross-validation by edge sampling’
by J Lei & K Z Lin - 289-292 Rejoinder: ‘Network cross-validation by edge sampling’
by Tianxi Li & Elizaveta Levina & Ji Zhu - 293-310 Adaptive nonparametric regression with the K-nearest neighbour fused lasso
by Oscar Hernan Madrid Padilla & James Sharpnack & Yanzhen Chen & Daniela M Witten - 311-330 Classification with imperfect training labels
by Timothy I Cannings & Yingying Fan & Richard J Samworth - 331-346 Testing conditional mean independence for functional data
by C E Lee & X Zhang & X Shao - 347-364 The essential histogram
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