Content
2021, Volume 108, Issue 2
- 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 - 211-227 Goodness-of-fit tests for the cure rate in a mixture cure model
by U U Müller & I Van Keilegom - 229-241 Semiparametric inference for the dominance index under the density ratio model
by W W Zhuang & B Y Hu & J Chen - 243-250 Signal-plus-noise matrix models: eigenvector deviations and fluctuations
by J Cape & M Tang & C E Priebe
2018, Volume 105, Issue 4
- 755-768 Selective inference with unknown variance via the square-root lasso
by Xiaoying Tian & Joshua R Loftus & Jonathan E Taylor - 769-782 A convex formulation for high-dimensional sparse sliced inverse regression
by Kean Ming Tan & Zhaoran Wang & Tong Zhang & Han Liu & R Dennis Cook - 783-795 A Durbin–Levinson regularized estimator of high-dimensional autocovariance matrices
by Tommaso Proietti & Alessandro Giovannelli - 797-814 Statistical sparsity
by Peter McCullagh & Nicholas G Polson - 815-831 A test of weak separability for multi-way functional data, with application to brain connectivity studies
by Brian Lynch & Kehui Chen - 833-848 A test for the absence of aliasing or local white noise in locally stationary wavelet time series
by I A Eckley & G P Nason - 849-858 Model-assisted design of experiments in the presence of network-correlated outcomes
by Guillaume W Basse & Edoardo M Airoldi - 859-872 Wild residual bootstrap inference for penalized quantile regression with heteroscedastic errors
by Lan Wang & Ingrid Van Keilegom & Adam Maidman - 873-890 A bootstrap recipe for post-model-selection inference under linear regression models
by S M S Lee & Y Wu - 891-903 The change-plane Cox model
by Susan Wei & Michael R Kosorok - 905-916 Transforming cumulative hazard estimates
by Pål C Ryalen & Mats J Stensrud & Kjetil Røysland - 917-930 Integrative linear discriminant analysis with guaranteed error rate improvement
by Quefeng Li & Lexin Li - 931-944 Continuous testing for Poisson process intensities: a new perspective on scanning statistics
by Franck Picard & Patricia Reynaud-Bouret & Etienne Roquain - 945-962 Functional prediction through averaging estimated functional linear regression models
by Xinyu Zhang & Jeng-Min Chiou & Yanyuan Ma - 963-977 Constructing dynamic treatment regimes over indefinite time horizons
by Ashkan Ertefaie & Robert L Strawderman - 979-986 Principal ignorability in mediation analysis: through and beyond sequential ignorability
by Laura Forastiere & Alessandra Mattei & Peng Ding - 987-993 Identifying causal effects with proxy variables of an unmeasured confounder
by Wang Miao & Zhi Geng & Eric J Tchetgen Tchetgen - 994-1000 Regression-assisted inference for the average treatment effect in paired experiments
by Colin B Fogarty
2018, Volume 105, Issue 3
- 505-516 Assessing replicability of findings across two studies of multiple features
by Marina Bogomolov & Ruth Heller - 517-527 When is the first spurious variable selected by sequential regression procedures?
by Weijie J Su - 529-546 Asymptotic normality of interpoint distances for high-dimensional data with applications to the two-sample problem
by Jun Li - 547-562 Symmetric rank covariances: a generalized framework for nonparametric measures of dependence
by L Weihs & M Drton & N Meinshausen - 563-574 Shrinking characteristics of precision matrix estimators
by Aaron J Molstad & Adam J Rothman - 575-592 High-dimensional peaks-over-threshold inference
by R de Fondeville & A C Davison - 593-607 Asymptotic properties of approximate Bayesian computation
by D T Frazier & G M Martin & C P Robert & J Rousseau - 609-625 Variance estimation in the particle filter
by A Lee & N Whiteley - 627-643 A structural break test for extremal dependence in β-mixing random vectors
by Y Hoga - 645-664 Asymptotic post-selection inference for the Akaike information criterion
by Ali Charkhi & Gerda Claeskens - 665-680 A semiparametric extension of the stochastic block model for longitudinal networks
by C Matias & T Rebafka & F Villers - 681-690 Local polynomial regression with correlated errors in random design and unknown correlation structure
by K De Brabanter & F Cao & I Gijbels & J Opsomer - 691-707 Bayesian spatial monotonic multiple regression
by C Rohrbeck & D A Costain & A Frigessi - 709-722 Covariate association eliminating weights: a unified weighting framework for causal effect estimation
by Sean Yiu & Li Su - 723-738 Targeted learning ensembles for optimal individualized treatment rules with time-to-event outcomes
by I Díaz & O Savenkov & K Ballman - 739-744 On Bayes factors for the linear model
by T S Shively & S G Walker - 745-752 Sequential rerandomization
by Quan Zhou & Philip A Ernst & Kari Lock Morgan & Donald B Rubin & Anru Zhang - 753-753 Amendments and Corrections
by F Blasques & S J Koopman & A Lucas
2018, Volume 105, Issue 2
- 249-269 Joint testing and false discovery rate control in high-dimensional multivariate regression
by Yin Xia & T Tony Cai & Hongzhe Li - 271-284 Robust estimation of high-dimensional covariance and precision matrices
by Marco Avella-Medina & Heather S Battey & Jianqing Fan & Quefeng Li - 285-299 On the asymptotic efficiency of approximate Bayesian computation estimators
by Wentao Li & Paul Fearnhead - 301-318 Convergence of regression-adjusted approximate Bayesian computation
by Wentao Li & Paul Fearnhead - 319-335 Adaptive multigroup confidence intervals with constant coverage
by C Yu & P D Hoff - 337-352 Testing independence for multivariate time series via the auto-distance correlation matrix
by K Fokianos & M Pitsillou - 353-369 A frequency domain analysis of the error distribution from noisy high-frequency data
by Jinyuan Chang & Aurore Delaigle & Peter Hall & Cheng Yong Tang - 371-388 Bayesian precision and covariance matrix estimation for graphical Gaussian models with edge and vertex symmetries
by H Massam & Q Li & X Gao - 389-402 On the number of principal components in high dimensions
by Sungkyu Jung & Myung Hee Lee & Jeongyoun Ahn - 403-418 Semiparametric regression analysis for composite endpoints subject to componentwise censoring
by Guoqing Diao & Donglin Zeng & Chunlei Ke & Haijun Ma & Qi Jiang & Joseph G Ibrahim - 419-429 Design-based maps for continuous spatial populations
by L Fattorini & M Marcheselli & C Pisani & L Pratelli - 431-446 Theoretical limits of microclustering for record linkage
by J E Johndrow & K Lum & D B Dunson - 447-454 On edge correction of conditional and intrinsic autoregressions
by D Mondal - 455-462 A non-model-based approach to bandwidth selection for kernel estimators of spatial intensity functions
by O Cronie & M N M Van Lieshout - 463-469 Bootstrapping volatility functionals: a local and nonparametric perspective
by Xin-Bing Kong & Shao-Jun Xu & Wang Zhou - 471-477 On the connection between maximin distance designs and orthogonal designs
by Yaping Wang & Jianfeng Yang & Hongquan Xu - 479-486 Optimal pseudolikelihood estimation in the analysis of multivariate missing data with nonignorable nonresponse
by Jiwei Zhao & Yanyuan Ma - 487-493 Asymptotic inference of causal effects with observational studies trimmed by the estimated propensity scores
by S Yang & P Ding - 495-501 Uniformly minimum variance conditionally unbiased estimation in multi-arm multi-stage clinical trials
by Nigel Stallard & Peter K Kimani - 503-503 ‘Asymptotic properties of penalized spline estimators’
by G Claeskens & T Krivobokova & J D Opsomer
2018, Volume 105, Issue 1
- 1-18 Dual regression
by R H Spady & S Stouli - 19-29 A structural Markov property for decomposable graph laws that allows control of clique intersections
by Peter J Green & Alun Thomas - 31-44 Robust and consistent variable selection in high-dimensional generalized linear models
by Marco Avella-Medina & Elvezio Ronchetti - 45-56 A randomization-based perspective on analysis of variance: a test statistic robust to treatment effect heterogeneity
by Peng Ding & Tirthankar Dasgupta