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Content
2022, Volume 109, Issue 2
- 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
by Housen Li & Axel Munk & Hannes Sieling & Guenther Walther - 365-380 Discontinuous Hamiltonian Monte Carlo for discrete parameters and discontinuous likelihoods
by Akihiko Nishimura & David B Dunson & Jianfeng Lu - 381-395 On the use of approximate Bayesian computation Markov chain Monte Carlo with inflated tolerance and post-correction
by Matti Vihola & Jordan Franks - 397-414 Lassoing eigenvalues
by David E Tyler & Mengxi Yi - 415-431 Doubly functional graphical models in high dimensions
by Xinghao Qiao & Cheng Qian & Gareth M James & Shaojun Guo - 433-448 Ensemble estimation and variable selection with semiparametric regression models
by Sunyoung Shin & Yufeng Liu & Stephen R Cole & Jason P Fine - 449-465 Estimation from cross-sectional data under a semiparametric truncation model
by C Heuchenne & J De Uña-Álvarez & G Laurent - 467-480 Robust empirical Bayes small area estimation with density power divergence
by S Sugasawa - 481-488 Estimation of error variance via ridge regression
by X Liu & S Zheng & X Feng - 489-496 On the marginal likelihood and cross-validation
by E Fong & C C Holmes - 497-504 Consistency for the tree bootstrap in respondent-driven sampling
by A K B Green & T H McCormick & A E Raftery - 505-511 A random-perturbation-based rank estimator of the number of factors
by Xinbing Kong
2020, Volume 107, Issue 1
- 1-23 The Hastings algorithm at fifty
by D B Dunson & J E Johndrow - 25-40 Scalable inference for crossed random effects models
by O Papaspiliopoulos & G O Roberts & G Zanella - 41-59 High-dimensional causal discovery under non-Gaussianity Abstract: Summary We consider graphical models based on a recursive system of linear structural equations. This implies that there is an ordering, $\sigma$, of the variables such that each observed variable $Y_v$ is a linear function of a variable-specific error term and the other observed variables $Y_u$ with $\sigma(u)
by Y Samuel Wang & Mathias Drton - 61-73 Consistent community detection in multi-layer network data
by Jing Lei & Kehui Chen & Brian Lynch - 75-92 Multisample estimation of bacterial composition matrices in metagenomics data
by Yuanpei Cao & Anru Zhang & Hongzhe Li - 93-105 Minimal dispersion approximately balancing weights: asymptotic properties and practical considerations
by Yixin Wang & Jose R Zubizarreta - 107-122 Model-free approach to quantifying the proportion of treatment effect explained by a surrogate marker
by Xuan Wang & Layla Parast & Lu Tian & Tianxi Cai - 123-136 Semiparametric estimation of structural failure time models in continuous-time processes
by S Yang & K Pieper & F Cools - 137-158 Regularized calibrated estimation of propensity scores with model misspecification and high-dimensional data
by Z Tan - 159-172 On semiparametric estimation of a path-specific effect in the presence of mediator-outcome confounding
by C H Miles & I Shpitser & P Kanki & S Meloni & E J Tchetgen Tchetgen - 173-190 A conditional density estimation partition model using logistic Gaussian processes
by R D Payne & N Guha & Y Ding & B K Mallick - 191-204 Bayesian constraint relaxation
by Leo L Duan & Alexander L Young & Akihiko Nishimura & David B Dunson - 205-221 Bayesian sparse multiple regression for simultaneous rank reduction and variable selection
by Antik Chakraborty & Anirban Bhattacharya & Bani K Mallick - 223-230 Simplified integrated nested Laplace approximation
by Simon N Wood - 231-237 Analysis of grouped data using conjugate generalized linear mixed models
by Jarod Y L Lee & Peter J Green & Louise M Ryan - 238-245 Measurement errors in the binary instrumental variable model
by Zhichao Jiang & Peng Ding - 246-253 Diagnosing missing always at random in multivariate data
by Iavor I Bojinov & Natesh S Pillai & Donald B Rubin - 255-255 ‘Variance estimation in the particle filter’
by A Lee & N Whiteley
2019, Volume 106, Issue 4
- 749-764 Fast exact conformalization of the lasso using piecewise linear homotopy
by J Lei - 765-779 Conjugate Bayes for probit regression via unified skew-normal distributions
by Daniele Durante - 781-801 Bootstrapping spectral statistics in high dimensions
by Miles E Lopes & Andrew Blandino & Alexander Aue - 803-821 Fréchet analysis of variance for random objects
by Paromita Dubey & Hans-Georg Müller - 823-840 Accounting for unobserved covariates with varying degrees of estimability in high-dimensional biological data
by Chris McKennan & Dan Nicolae - 841-856 Simultaneous control of all false discovery proportions in large-scale multiple hypothesis testing
by Jelle J Goeman & Rosa J Meijer & Thijmen J P Krebs & Aldo Solari - 857-873 Network dependence testing via diffusion maps and distance-based correlations
by Youjin Lee & Cencheng Shen & Carey E Priebe & Joshua T Vogelstein - 875-888 Causal inference with confounders missing not at random
by S Yang & L Wang & P Ding - 889-911 Sequentially additive nonignorable missing data modelling using auxiliary marginal information
by Mauricio Sadinle & Jerome P Reiter - 913-927 Tyler shape depth
by D Paindaveine & G Van Bever - 929-940 Testing for arbitrary interference on experimentation platforms
by J Pouget-Abadie & G Saint-Jacques & M Saveski & W Duan & S Ghosh & Y Xu & E M Airoldi - 941-956 Semiparametric segment M-estimation for locally stationary diffusions
by P -Y Deléamont & D La Vecchia - 957-964 Distributional consistency of the lasso by perturbation bootstrap
by Debraj Das & S N Lahiri - 965-972 Within-cluster resampling for multilevel models under informative cluster size
by D Lee & J K Kim & C J Skinner - 973-980 On causal discovery with an equal-variance assumption
by Wenyu Chen & Mathias Drton & Y Samuel Wang - 981-988 Bayesian jackknife empirical likelihood
by Y Cheng & Y Zhao - 989-996 On nonparametric maximum likelihood estimation with double truncation
by J Xiao & M G Hudgens - 997-1004 Column-orthogonal strong orthogonal arrays of strength two plus and three minus
by Yongdao Zhou & Boxin Tang
2019, Volume 106, Issue 2
- 251-266 The debiased Whittle likelihood
by Adam M Sykulski & Sofia C Olhede & Arthur P Guillaumin & Jonathan M Lilly & Jeffrey J Early - 267-286 Spectral density estimation for random fields via periodic embeddings
by Joseph Guinness - 287-302 Unbiased Hamiltonian Monte Carlo with couplings
by J Heng & P E Jacob - 303-319 Kinetic energy choice in Hamiltonian/hybrid Monte Carlo
by S Livingstone & M F Faulkner & G O Roberts - 321-337 Multivariate output analysis for Markov chain Monte Carlo
by Dootika Vats & James M Flegal & Galin L Jones - 339-351 Wasserstein covariance for multiple random densities
by Alexander Petersen & Hans-Georg Müller - 353-367 Integrating the evidence from evidence factors in observational studies
by B Karmakar & B French & D S Small - 369-384 Pseudo-population bootstrap methods for imputed survey data
by S Chen & D Haziza & C Léger & Z Mashreghi - 385-400 Bootstrap of residual processes in regression: to smooth or not to smooth?
by N Neumeyer & I Van Keilegom - 401-416 Differential Markov random field analysis with an application to detecting differential microbial community networks
by T T Cai & H Li & J Ma & Y Xia - 417-432 Sufficient direction factor model and its application to gene expression quantitative trait loci discovery
by F Jiang & Y Ma & Y Wei - 433-452 Identifiability and estimation of structural vector autoregressive models for subsampled and mixed-frequency time series
by A Tank & E B Fox & A Shojaie - 453-464 Interleaved lattice-based maximin distance designs
by Xu He - 465-478 General Bayesian updating and the loss-likelihood bootstrap
by S P Lyddon & C C Holmes & S G Walker - 479-486 Calibrating general posterior credible regions
by Nicholas Syring & Ryan Martin - 487-494 Randomization tests of causal effects under interference
by G W Basse & A Feller & P Toulis - 495-500 Hierarchical Bayes versus empirical Bayes density predictors under general divergence loss
by M Ghosh & T Kubokawa
2019, Volume 106, Issue 1
- 1-18 Gene hunting with hidden Markov model knockoffs
by M Sesia & C Sabatti & E J Candès - 19-22 Discussion of ‘Gene hunting with hidden Markov model knockoffs’
by L Bottolo & S Richardson - 23-26 Discussion of ‘Gene hunting with hidden Markov model knockoffs’
by S W Jewell & D M Witten - 27-28 Discussion of ‘Gene hunting with hidden Markov model knockoffs’
by J L Marchini - 29-33 Discussion of ‘Gene hunting with hidden Markov model knockoffs’
by Jonathan D Rosenblatt & Ya’acov Ritov & Jelle J Goeman - 35-45 Rejoinder: ‘Gene hunting with hidden Markov model knockoffs’
by M Sesia & C Sabatti & E J Candès - 47-68 Testing for independence in arbitrary distributions
by C Genest & J G Nešlehová & B Rémillard & O A Murphy - 69-86 A sequential algorithm for false discovery rate control on directed acyclic graphs
by Aaditya Ramdas & Jianbo Chen & Martin J Wainwright & Michael I Jordan - 87-107 Nonparametric regression with adaptive truncation via a convex hierarchical penalty
by Asad Haris & Ali Shojaie & Noah Simon - 109-125 Constrained likelihood for reconstructing a directed acyclic Gaussian graph
by Yiping Yuan & Xiaotong Shen & Wei Pan & Zizhuo Wang - 127-144 Extremal behaviour of aggregated data with an application to downscaling
by Sebastian Engelke & Raphaël De Fondeville & Marco Oesting - 145-160 Recovering covariance from functional fragments
by M-H Descary & V M Panaretos - 161-180 Classification of functional fragments by regularized linear classifiers with domain selection
by David Kraus & Marco Stefanucci - 181-196 Counting process-based dimension reduction methods for censored outcomes
by Qiang Sun & Ruoqing Zhu & Tao Wang & Donglin Zeng - 197-210 Low-risk population size estimates in the presence of capture heterogeneity
by J E Johndrow & K Lum & D Manrique-Vallier