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Content
2024, Volume 111, Issue 4
- 1089-1108 Optimal regimes for algorithm-assisted human decision-making
by M J Stensrud & J D Laurendeau & A L Sarvet - 1109-1127 Exact selective inference with randomization
by Snigdha Panigrahi & Kevin Fry & Jonathan Taylor - 1129-1150 Flexible control of the median of the false discovery proportion
by Jesse Hemerik & Aldo Solari & Jelle J Goeman - 1151-1167 Radial neighbours for provably accurate scalable approximations of Gaussian processes
by Yichen Zhu & Michele Peruzzi & Cheng Li & David B Dunson - 1169-1186 A rank-based sequential test of independence
by Alexander Henzi & Michael Law - 1187-1199 Testing independence for sparse longitudinal data
by Changbo Zhu & Junwen Yao & Jane-Ling Wang - 1201-1219 On some algorithms for estimation in Gaussian graphical models
by S Højsgaard & S Lauritzen - 1221-1240 Network-adjusted covariates for community detection
by Y Hu & W Wang - 1241-1256 Skip sampling: subsampling in the frequency domain
by Tucker McElroy & Dimitris N Politis - 1257-1275 Individualized dynamic latent factor model for multi-resolutional data with application to mobile health
by J Zhang & F Xue & Q Xu & J Lee & A Qu - 1277-1292 Difference-based covariance matrix estimation in time series nonparametric regression with application to specification tests
by Lujia Bai & Weichi Wu - 1293-1312 Testing serial dependence or cross dependence for time series with underreporting
by Keyao Wei & Lengyang Wang & Yingcun Xia - 1313-1329 Debiasing Welch’s method for spectral density estimation
by Lachlan C Astfalck & Adam M Sykulski & Edward J Cripps - 1331-1348 Bootstrap test procedure for variance components in nonlinear mixed effects models in the presence of nuisance parameters and a singular Fisher information matrix
by T Guédon & C Baey & E Kuhn - 1349-1368 Sensitivity analysis for matched observational studies with continuous exposures and binary outcomes
by Jeffrey Zhang & Dylan S Small & Siyu Heng - 1369-1386 A model-free variable screening method for optimal treatment regimes with high-dimensional survival data
by Cheng-Han Yang & Yu-Jen Cheng - 1387-1404 Inference for possibly misspecified generalized linear models with nonpolynomial-dimensional nuisance parameters
by Shaoxin Hong & Jiancheng Jiang & Xuejun Jiang & Haofeng Wang - 1405-1412 More power by using fewer permutations
by Nick W Koning - 1413-1420 Covariate adjustment in randomized experiments with missing outcomes and covariates
by Anqi Zhao & Peng Ding & Fan Li - 1421-1428 On propensity score matching with a diverging number of matches
by Yihui He & Fang Han - 1429-1436 Sharp symbolic nonparametric bounds for measures of benefit in observational and imperfect randomized studies with ordinal outcomes
by Erin E Gabriel & Michael C Sachs & Andreas Kryger Jensen - 1437-1444 Inference for partial correlations of a multivariate Gaussian time series
by A S Dilernia & M Fiecas & L Zhang
2024, Volume 111, Issue 3
- 727-742 Selective conformal inference with false coverage-statement rate control
by Yajie Bao & Yuyang Huo & Haojie Ren & Changliang Zou - 743-754 Central limit theorems for local network statistics
by P A Maugis - 755-770 Generalized kernel two-sample tests
by Hoseung Song & Hao Chen - 771-788 Graphical tools for selecting conditional instrumental sets
by L Henckel & M Buttenschoen & M H Maathuis - 789-808 Doubly robust estimation under covariate-induced dependent left truncation
by Yuyao Wang & Andrew Ying & Ronghui Xu - 809-823 Explicit solutions for the asymptotically optimal bandwidth in cross-validation
by Karim M Abadir & Michel Lubrano - 825-842 Asymptotically constant risk estimator of the time-average variance constant
by K W Chan & C Y Yau - 843-864 Efficient nonparametric estimation of Toeplitz covariance matrices
by K Klockmann & T Krivobokova - 865-880 On the optimality of score-driven models
by P Gorgi & C S A Lauria & A Luati - 881-902 Phylogenetic association analysis with conditional rank correlation
by Shulei Wang & Bo Yuan & T Tony Cai & Hongzhe Li - 903-923 Network community detection using higher-order structures
by X Yu & J Zhu - 925-944 Testing serial independence of object-valued time series
by Feiyu Jiang & Hanjia Gao & Xiaofeng Shao - 945-969 Nonparametric priors with full-range borrowing of information
by F Ascolani & B Franzolini & A Lijoi & I Prünster - 971-988 Maximum likelihood estimation for semiparametric regression models with interval-censored multistate data
by Yu Gu & Donglin Zeng & Gerardo Heiss & D Y Lin - 989-1011 On inference in high-dimensional logistic regression models with separated data
by R M Lewis & H S Battey - 1013-1027 Projective independence tests in high dimensions: the curses and the cures
by Yaowu Zhang & Liping Zhu - 1029-1045 Familial inference: tests for hypotheses on a family of centres
by Ryan Thompson & Catherine S Forbes & Steven N MacEachern & Mario Peruggia - 1047-1061 Regression analysis of group-tested current status data
by Shuwei Li & Tao Hu & Lianming Wang & Christopher S McMahan & Joshua M Tebbs - 1063-1070 On the failure of the bootstrap for Chatterjee’s rank correlation
by Zhexiao Lin & Fang Han - 1071-1075 A note on minimax robustness of designs against correlated or heteroscedastic responses
by D P Wiens - 1077-1084 Second term improvement to generalized linear mixed model asymptotics
by Luca Maestrini & Aishwarya Bhaskaran & Matt P Wand
2024, Volume 111, Issue 2
- 367-391 The state of cumulative sum sequential changepoint testing 70 years after Page
by Alexander Aue & Claudia Kirch - 393-416 On selection and conditioning in multiple testing and selective inference
by Jelle J Goeman & Aldo Solari - 417-439 E-values as unnormalized weights in multiple testing
by Nikolaos Ignatiadis & Ruodu Wang & Aaditya Ramdas - 441-458 More efficient exact group invariance testing: using a representative subgroup
by N W Koning & J Hemerik - 459-477 Conformalized survival analysis with adaptive cut-offs
by Yu Gui & Rohan Hore & Zhimei Ren & Rina Foygel Barber - 479-496 τ-censored weighted Benjamini–Hochberg procedures under independence
by Haibing Zhao & Huijuan Zhou - 497-516 Kernel methods for causal functions: dose, heterogeneous and incremental response curves
by R Singh & L Xu & A Gretton - 517-535 Selective machine learning of doubly robust functionals
by Y Cui & E J Tchetgen Tchetgen - 537-550 Promises of parallel outcomes
by Ying Zhou & Dingke Tang & Dehan Kong & Linbo Wang - 551-572 Order-based structure learning without score equivalence
by Hyunwoong Chang & James J Cai & Quan Zhou - 573-589 Retrospective causal inference with multiple effect variables
by Wei Li & Zitong Lu & Jinzhu Jia & Min Xie & Zhi Geng - 591-607 Likelihood-based inference under nonconvex boundary constraints
by J Y Wang & Z S Ye & Y Chen - 609-623 On varimax asymptotics in network models and spectral methods for dimensionality reduction
by J Cape - 625-641 A cross-validation-based statistical theory for point processes
by Ottmar Cronie & Mehdi Moradi & Christophe A N Biscio - 643-660 Estimation of prediction error in time series
by Alexander Aue & Prabir Burman - 661-676 An eigenvector-assisted estimation framework for signal-plus-noise matrix models
by Fangzheng Xie & Dingbo Wu - 677-689 An anomaly arising in the analysis of processes with more than one source of variability
by H S Battey & Peter McCullagh - 691-705 Covariate-adjusted log-rank test: guaranteed efficiency gain and universal applicability
by Ting Ye & Jun Shao & Yanyao Yi - 707-714 Deep Kronecker network
by Long Feng & Guang Yang - 715-722 Kernel interpolation generalizes poorly
by Yicheng Li & Haobo Zhang & Qian Lin
2024, Volume 111, Issue 1
- 1-15 Causal inference with misspecified exposure mappings: separating definitions and assumptions
by F Sävje - 17-20 Discussion of ‘Causal inference with misspecified exposure mappings: separating definitions and assumptions’
by Michael P Leung - 21-24 Discussion of ‘Causal inference with misspecified exposure mappings: separating definitions and assumptions’
by Eric Auerbach & Jonathan Auerbach & Max Tabord-Meehan - 25-29 Rejoinder: Causal inference with misspecified exposure mappings: separating definitions and assumptions
by F Sävje - 31-50 A linear adjustment-based approach to posterior drift in transfer learning
by Subha Maity & Diptavo Dutta & Jonathan Terhorst & Yuekai Sun & Moulinath Banerjee - 51-69 Efficient evaluation of natural stochastic policies in off-line reinforcement learning
by Nathan Kallus & Masatoshi Uehara - 71-92 Universal robust regression via maximum mean discrepancy
by P Alquier & M Gerber - 93-108 Online inference with debiased stochastic gradient descent
by Ruijian Han & Lan Luo & Yuanyuan Lin & Jian Huang - 109-127 Hybrid confidence intervals for informative uniform asymptotic inference after model selection
by A McCloskey - 129-145 One-step targeted maximum likelihood estimation for targeting cause-specific absolute risks and survival curves
by H C W Rytgaard & M J van der Laan - 147-170 Populations of unlabelled networks: graph space geometry and generalized geodesic principal components
by Anna Calissano & Aasa Feragen & Simone Vantini - 171-193 Statistical summaries of unlabelled evolutionary trees
by Rajanala Samyak & Julia A Palacios - 195-214 Bayesian learning of network structures from interventional experimental data
by F Castelletti & S Peluso - 215-233 Tailored inference for finite populations: conditional validity and transfer across distributions
by Ying Jin & Dominik Rothenhäusler - 235-254 Treatment effect quantiles in stratified randomized experiments and matched observational studies
by Yongchang Su & Xinran Li - 255-272 A mark-specific quantile regression model
by Lianqiang Qu & Liuquan Sun & Yanqing Sun - 273-289 On geometric convergence for the Metropolis-adjusted Langevin algorithm under simple conditions
by Alain Oliviero-Durmus & Éric Moulines - 291-308 Interpolating discriminant functions in high-dimensional Gaussian latent mixtures
by Xin Bing & Marten Wegkamp - 309-329 Robust sample weighting to facilitate individualized treatment rule learning for a target population
by Rui Chen & Jared D Huling & Guanhua Chen & Menggang Yu - 331-338 No-harm calibration for generalized Oaxaca–Blinder estimators
by P L Cohen & C B Fogarty - 339-346 Characterizing M-estimators
by Timo Dimitriadis Alfred Weber & Tobias FisslerRiskLab & Johanna Ziegel - 347-354 Scalable subsampling: computation, aggregation and inference
by Dimitris N Politis - 355-363 Power and sample size calculations for rerandomization
by Zach Branson & inran Li & Peng Ding
2023, Volume 110, Issue 4
- 841-858 Statistical inference for streamed longitudinal data
by Lan Luo & Jingshen Wang & Emily C Hector - 859-862 Discussion of ‘Statistical inference for streamed longitudinal data’
by Peter X-K Song & Ling Zhou - 863-866 Discussion of ‘Statistical inference for streamed longitudinal data’
by J Wang & H Wang & K Chen - 867-869 Discussion of ‘Statistical inference for streamed longitudinal data’
by Yang Ning & Jingyi Duan - 871-874 Rejoinder: ‘Statistical inference for streamed longitudinal data’
by Lan Luo & Jingshen Wang & Emily C Hector - 875-896 Semiparametric counterfactual density estimation
by E H Kennedy & S Balakrishnan & L A Wasserman - 897-911 Soft calibration for selection bias problems under mixed-effects models
by Chenyin Gao & Shu Yang & Jae Kwang Kim - 913-931 Targeted optimal treatment regime learning using summary statistics
by J Chu & W Lu & S Yang - 933-952 Sampling distribution for single-regression Granger causality estimators
by A J Gutknecht & L Barnett - 953-971 Semiparametric efficient G-estimation with invalid instrumental variables
by B Sun & Z Liu & E J Tchetgen - 973-987 Proximal mediation analysis
by Oliver Dukes & Ilya Shpitser & Eric J Tchetgen - 989-1008 An instrumental variable method for point processes: generalized Wald estimation based on deconvolution
by Zhichao Jiang & Shizhe Chen & Peng Ding - 1009-1021 Nonparametric estimation of the intensity function of a spatial point process on a Riemannian manifold
by S Ward & H S Battey & E A K Cohen - 1023-1040 A robust fusion-extraction procedure with summary statistics in the presence of biased sources
by Ruoyu Wang & Qihua Wang & Wang Miao - 1041-1054 The surrogate index: Combining short-term proxies to estimate long-term treatment effects more rapidly and precisely
by Sijia Li & Alex Luedtke - 1055-1076 Equivariant estimation of Fréchet means
by A McCormack & P D Hoff - 1077-1098 -estimation for smooth eigenvectors of matrix-valued functions
by Giovanni Motta & Wei Biao Wu & Mohsen Pourahmadi - 1099-1115 A subsampling perspective for extending the validity of state-of-the-art bootstraps in the frequency domain
by Haihan Yu & Mark S Kaiser & Daniel J Nordman - 1117-1124 Ancestor regression in linear structural equation models
by C Schultheiss & P Bühlmann
2023, Volume 110, Issue 3
- 559-578 A generalized Bayes framework for probabilistic clustering
by Tommaso Rigon & Amy H Herring & David B Dunson - 579-595 Optimal design of the Barker proposal and other locally balanced Metropolis–Hastings algorithms
by Jure Vogrinc & Samuel Livingstone & Giacomo Zanella - 597-614 Splitting strategies for post-selection inference
by D García Rasines & G A Young - 615-629 On the implied weights of linear regression for causal inference
by Ambarish Chattopadhyay & José R Zubizarreta - 631-644 On the statistical role of inexact matching in observational studies
by Kevin Guo & Dominik Rothenhäusler - 645-662 Assessing time-varying causal effect moderation in the presence of cluster-level treatment effect heterogeneity and interference
by J Shi & Z Wu & W Dempsey - 663-680 Honest calibration assessment for binary outcome predictions
by Timo Dimitriadis & Lutz Dümbgen & Alexander Henzi & Marius Puke & Johanna Ziegel - 681-697 Thresholded graphical lasso adjusts for latent variables
by Minjie Wang & Genevera I Allen - 699-719 Spectral adjustment for spatial confounding
by Yawen Guan & Garritt L Page & Brian J Reich & Massimo Ventrucci & Shu Yang - 721-738 Dependent censoring based on parametric copulas
by C Czado & I Van Keilegom - 739-761 Variable elimination, graph reduction and the efficient g-formula
by F Richard Guo & Emilija Perković & Andrea Rotnitzky - 763-776 Existence of matching priors on compact spaces
by Haosui Duanmu & Daniel M Roy & Aaron Smith - 777-797 High-dimensional analysis of variance in multivariate linear regression
by Zhipeng Lou & Xianyang Zhang & Wei Biao Wu - 799-814 Testing Kronecker product covariance matrices for high-dimensional matrix-variate data
by Long Yu & Jiahui Xie & Wang Zhou - 815-830 Marginal proportional hazards models for multivariate interval-censored data
by Yangjianchen Xu & Donglin Zeng & D Y Lin - 831-838 Median regularity and honest inference
by Arun Kumar Kuchibhotla & Sivaraman Balakrishnan & Larry Wasserman
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