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November 2019, Volume 81, Issue 5
- 861-880 Non‐parametric cure rate estimation under insufficient follow‐up by using extremes
by Mikael Escobar‐Bach & Ingrid Van Keilegom - 881-900 On the design of experiments with ordered treatments
by Satya Prakash Singh & Ori Davidov - 901-931 Tensor graphical lasso (TeraLasso)
by Kristjan Greenewald & Shuheng Zhou & Alfred Hero
September 2019, Volume 81, Issue 4
- 675-705 High dimensional linear discriminant analysis: optimality, adaptive algorithm and missing data
by T. Tony Cai & Linjun Zhang - 707-734 Signal classification for the integrative analysis of multiple sequences of large‐scale multiple tests
by Dongdong Xiang & Sihai Dave Zhao & T. Tony Cai - 735-761 Sensitivity analysis for inverse probability weighting estimators via the percentile bootstrap
by Qingyuan Zhao & Dylan S. Small & Bhaswar B. Bhattacharya - 763-779 MALMEM: model averaging in linear measurement error models
by Xinyu Zhang & Yanyuan Ma & Raymond J. Carroll - 781-804 Dynamic shrinkage processes
by Daniel R. Kowal & David S. Matteson & David Ruppert - 805-806 Corrigendum: Detecting heteroscedasticity in non‐parametric regression using weighted empirical processes
by Justin Chown & Ursula U. Müller
July 2019, Volume 81, Issue 3
- 459-487 Robust causal structure learning with some hidden variables
by Benjamin Frot & Preetam Nandy & Marloes H. Maathuis - 489-517 Scalable importance tempering and Bayesian variable selection
by Giacomo Zanella & Gareth Roberts - 519-545 Computer model calibration with confidence and consistency
by Matthew Plumlee - 547-573 Post‐selection estimation and testing following aggregate association tests
by Ruth Heller & Amit Meir & Nilanjan Chatterjee - 575-602 A general asymptotic framework for distribution‐free graph‐based two‐sample tests
by Bhaswar B. Bhattacharya - 603-627 Intrinsic Gaussian processes on complex constrained domains
by Mu Niu & Pokman Cheung & Lizhen Lin & Zhenwen Dai & Neil Lawrence & David Dunson - 629-648 Lack‐of‐fit tests for quantile regression models
by Chen Dong & Guodong Li & Xingdong Feng - 649-672 Narrowest‐over‐threshold detection of multiple change points and change‐point‐like features
by Rafal Baranowski & Yining Chen & Piotr Fryzlewicz
April 2019, Volume 81, Issue 2
- 187-234 Covariate‐assisted ranking and screening for large‐scale two‐sample inference
by T. Tony Cai & Wenguang Sun & Weinan Wang - 235-269 Approximate Bayesian computation with the Wasserstein distance
by Espen Bernton & Pierre E. Jacob & Mathieu Gerber & Christian P. Robert - 271-304 Clustering functional data into groups by using projections
by Aurore Delaigle & Peter Hall & Tung Pham - 305-333 A general framework for quantile estimation with incomplete data
by Peisong Han & Linglong Kong & Jiwei Zhao & Xingcai Zhou - 335-360 Construction of row–column factorial designs
by J. D. Godolphin - 361-384 Hypoelliptic diffusions: filtering and inference from complete and partial observations
by Susanne Ditlevsen & Adeline Samson - 385-408 Multiple influential point detection in high dimensional regression spaces
by Junlong Zhao & Chao Liu & Lu Niu & Chenlei Leng - 409-429 Semiparametric model for bivariate survival data subject to biased sampling
by Jin Piao & Jing Ning & Yu Shen - 431-456 Statistical inference for the population landscape via moment‐adjusted stochastic gradients
by Tengyuan Liang & Weijie J. Su
February 2019, Volume 81, Issue 1
- 3-4 Report of the Editors—2018
by David Dunson & Simon Wood - 5-43 Moment conditions and Bayesian non‐parametrics
by Luke Bornn & Neil Shephard & Reza Solgi - 45-74 Multiple testing with the structure‐adaptive Benjamini–Hochberg algorithm
by Ang Li & Rina Foygel Barber - 75-99 An omnibus non‐parametric test of equality in distribution for unknown functions
by Alex Luedtke & Marco Carone & Mark J. van der Laan - 101-120 Characterization of c‐, L‐ and ϕk‐optimal designs for a class of non‐linear multiple‐regression models
by Dennis Schmidt - 121-143 Robust causal inference with continuous instruments using the local instrumental variable curve
by Edward H. Kennedy & Scott Lorch & Dylan S. Small - 145-161 On cross‐validation for sparse reduced rank regression
by Yiyuan She & Hoang Tran - 163-183 Deterministic parallel analysis: an improved method for selecting factors and principal components
by Edgar Dobriban & Art B. Owen
November 2018, Volume 80, Issue 5
- 839-870 The correlated pseudomarginal method
by George Deligiannidis & Arnaud Doucet & Michael K. Pitt - 871-898 Random‐walk models of network formation and sequential Monte Carlo methods for graphs
by Benjamin Bloem‐Reddy & Peter Orbanz - 899-926 An imputation–regularized optimization algorithm for high dimensional missing data problems and beyond
by Faming Liang & Bochao Jia & Jingnan Xue & Qizhai Li & Ye Luo - 927-950 Multiple matrix Gaussian graphs estimation
by Yunzhang Zhu & Lexin Li - 951-974 Detecting heteroscedasticity in non‐parametric regression using weighted empirical processes
by Justin Chown & Ursula U. Müller - 975-993 Hybrid quantile regression estimation for time series models with conditional heteroscedasticity
by Yao Zheng & Qianqian Zhu & Guodong Li & Zhijie Xiao - 995-1014 Full likelihood inference for abundance from continuous time capture–recapture data
by Yang Liu & Yukun Liu & Pengfei Li & Jing Qin - 1015-1034 False discovery rate control for high dimensional networks of quantile associations conditioning on covariates
by Jichun Xie & Ruosha Li - 1035-1056 On mitigating the analytical limitations of finely stratified experiments
by Colin B. Fogarty - 1057-1086 Sparse generalized eigenvalue problem: optimal statistical rates via truncated Rayleigh flow
by Kean Ming Tan & Zhaoran Wang & Han Liu & Tong Zhang - 1087-1110 Bayesian regression tree ensembles that adapt to smoothness and sparsity
by Antonio R. Linero & Yun Yang
September 2018, Volume 80, Issue 4
- 597-623 Approximate residual balancing: debiased inference of average treatment effects in high dimensions
by Susan Athey & Guido W. Imbens & Stefan Wager - 625-648 Semiparametrically efficient estimation in quantile regression of secondary analysis
by Liang Liang & Yanyuan Ma & Ying Wei & Raymond J. Carroll - 649-679 AdaPT: an interactive procedure for multiple testing with side information
by Lihua Lei & William Fithian - 681-702 Maximin projection learning for optimal treatment decision with heterogeneous individualized treatment effects
by Chengchun Shi & Rui Song & Wenbin Lu & Bo Fu - 703-726 Estimated Wold representation and spectral‐density‐driven bootstrap for time series
by Jonas Krampe & Jens‐Peter Kreiss & Efstathios Paparoditis - 727-747 Bayesian inference for Gaussian graphical models beyond decomposable graphs
by Kshitij Khare & Bala Rajaratnam & Abhishek Saha - 749-767 Auxiliary gradient‐based sampling algorithms
by Michalis K. Titsias & Omiros Papaspiliopoulos - 769-791 Modelling non‐stationary multivariate time series of counts via common factors
by Fangfang Wang & Haonan Wang - 793-815 Confidence intervals for causal effects with invalid instruments by using two‐stage hard thresholding with voting
by Zijian Guo & Hyunseung Kang & T. Tony Cai & Dylan S. Small - 817-836 Asymptotic properties and information criteria for misspecified generalized linear mixed models
by Dalei Yu & Xinyu Zhang & Kelvin K. W. Yau
June 2018, Volume 80, Issue 3
- 455-480 Testing mutual independence in high dimension via distance covariance
by Shun Yao & Xianyang Zhang & Xiaofeng Shao - 481-508 Random networks, graphical models and exchangeability
by Steffen Lauritzen & Alessandro Rinaldo & Kayvan Sadeghi - 509-529 Detecting and dating structural breaks in functional data without dimension reduction
by Alexander Aue & Gregory Rice & Ozan Sönmez - 531-550 Bounded, efficient and multiply robust estimation of average treatment effects using instrumental variables
by Linbo Wang & Eric Tchetgen Tchetgen - 551-577 Panning for gold: ‘model‐X’ knockoffs for high dimensional controlled variable selection
by Emmanuel Candès & Yingying Fan & Lucas Janson & Jinchi Lv - 579-594 Semi‐supervised approaches to efficient evaluation of model prediction performance
by Jessica L. Gronsbell & Tianxi Cai
March 2018, Volume 80, Issue 2
- 263-292 Estimation of tail risk based on extreme expectiles
by Abdelaati Daouia & Stéphane Girard & Gilles Stupfler - 293-318 On structure testing for component covariance matrices of a high dimensional mixture
by Weiming Li & Jianfeng Yao - 319-342 From multiple Gaussian sequences to functional data and beyond: a Stein estimation approach
by Mark Koudstaal & Fang Yao - 343-364 Unified empirical likelihood ratio tests for functional concurrent linear models and the phase transition from sparse to dense functional data
by Honglang Wang & Ping‐Shou Zhong & Yuehua Cui & Yehua Li - 365-386 A block model for node popularity in networks with community structure
by Srijan Sengupta & Yuguo Chen - 387-408 Matrix variate regressions and envelope models
by Shanshan Ding & R. Dennis Cook - 409-432 Semiparametric dynamic max‐copula model for multivariate time series
by Zifeng Zhao & Zhengjun Zhang - 433-452 Testing for marginal linear effects in quantile regression
by Huixia Judy Wang & Ian W. McKeague & Min Qian
January 2018, Volume 80, Issue 1
- 3-4 Report of the Editors—2017
by David Dunson & Piotr Fryzlewicz - 5-31 Kernel‐based tests for joint independence
by Niklas Pfister & Peter Bühlmann & Bernhard Schölkopf & Jonas Peters - 33-56 Statistical inference based on randomly generated auxiliary variables
by Barry Schouten - 57-83 High dimensional change point estimation via sparse projection
by Tengyao Wang & Richard J. Samworth - 85-112 Optimal a priori balance in the design of controlled experiments
by Nathan Kallus - 113-135 Goodness‐of‐fit tests for high dimensional linear models
by Rajen D. Shah & Peter Bühlmann - 137-155 False discovery proportion estimation by permutations: confidence for significance analysis of microarrays
by Jesse Hemerik & Jelle J. Goeman - 157-175 Exact Bayesian inference in spatiotemporal Cox processes driven by multivariate Gaussian processes
by Flávio B. Gonçalves & Dani Gamerman - 177-198 Another look at distance‐weighted discrimination
by Boxiang Wang & Hui Zou - 199-217 Expectation propagation in the large data limit
by Guillaume Dehaene & Simon Barthelmé - 219-238 Inference for empirical Wasserstein distances on finite spaces
by Max Sommerfeld & Axel Munk - 239-260 A geometric approach to confidence regions and bands for functional parameters
by Hyunphil Choi & Matthew Reimherr
November 2017, Volume 79, Issue 5
- 1295-1366 Sparse graphs using exchangeable random measures
by François Caron & Emily B. Fox - 1367-1389 A coverage theory for least squares
by Algo Carè & Simone Garatti & Marco C. Campi - 1391-1414 Parameter stability and semiparametric inference in time varying auto-regressive conditional heteroscedasticity models
by Lionel Truquet - 1415-1437 Testing and confidence intervals for high dimensional proportional hazards models
by Ethan X. Fang & Yang Ning & Han Liu - 1439-1462 A Bayesian decision theoretic model of sequential experimentation with delayed response
by Stephen Chick & Martin Forster & Paolo Pertile - 1463-1485 Rank-based procedures in factorial designs: hypotheses about non-parametric treatment effects
by Edgar Brunner & Frank Konietschke & Markus Pauly & Madan L. Puri - 1487-1508 Semiparametric dose finding methods
by M. Clertant & J. O’Quigley - 1509-1525 Robust estimation of encouragement design intervention effects transported across sites
by Kara E. Rudolph & Mark J. Laan - 1527-1546 Convex clustering via l 1 fusion penalization
by Peter Radchenko & Gourab Mukherjee - 1547-1563 Optimal group testing designs for estimating prevalence with uncertain testing errors
by Shih-Hao Huang & Mong-Na Lo Huang & Kerby Shedden & Weng Kee Wong - 1565-1582 Concordance-assisted learning for estimating optimal individualized treatment regimes
by Caiyun Fan & Wenbin Lu & Rui Song & Yong Zhou - 1583-1599 Joint non-parametric correction estimator for excess relative risk regression in survival analysis with exposure measurement error
by Ching-Yun Wang & Harry Cullings & Xiao Song & Kenneth J. Kopecky - 1601-1618 Estimation of the common mean from heterogeneous normal observations with unknown variances
by Andrew L. Rukhin - 1619-1643 Quantile spectral analysis for locally stationary time series
by Stefan Birr & Stanislav Volgushev & Tobias Kley & Holger Dette & Marc Hallin - 1645-1666 Direct and indirect treatment effects–causal chains and mediation analysis with instrumental variables
by Markus Frölich & Martin Huber
September 2017, Volume 79, Issue 4
- 959-1035 Random-projection ensemble classification
by Timothy I. Cannings & Richard J. Samworth - 1037-1065 EigenPrism: inference for high dimensional signal-to-noise ratios
by Lucas Janson & Rina Foygel Barber & Emmanuel Candès - 1067-1093 Detection of adaptive shifts on phylogenies by using shifted stochastic processes on a tree
by Paul Bastide & Mahendra Mariadassou & Stéphane Robin - 1095-1118 A minimum relative entropy based correlation model between the response and covariates
by Bhaskar Bhattacharya & Mohammad Al-talib - 1119-1141 Statistical clustering of temporal networks through a dynamic stochastic block model
by Catherine Matias & Vincent Miele - 1143-1164 Estimation of the false discovery proportion with unknown dependence
by Jianqing Fan & Xu Han - 1165-1185 On estimation of optimal treatment regimes for maximizing t-year survival probability
by Runchao Jiang & Wenbin Lu & Rui Song & Marie Davidian - 1187-1206 Change point estimation in high dimensional Markov random-field models
by Sandipan Roy & Yves Atchadé & George Michailidis - 1207-1227 Heterogeneous change point inference
by Florian Pein & Hannes Sieling & Axel Munk - 1229-1245 Non-parametric methods for doubly robust estimation of continuous treatment effects
by Edward H. Kennedy & Zongming Ma & Matthew D. McHugh & Dylan S. Small - 1247-1268 The p-filter: multilayer false discovery rate control for grouped hypotheses
by Rina Foygel Barber & Aaditya Ramdas - 1269-1292 Maximum likelihood estimation for linear Gaussian covariance models
by Piotr Zwiernik & Caroline Uhler & Donald Richards
June 2017, Volume 79, Issue 3
- 651-676 Theoretical guarantees for approximate sampling from smooth and log-concave densities
by Arnak S. Dalalyan - 677-693 High dimensional correlation matrices: the central limit theorem and its applications
by Jiti Gao & Xiao Han & Guangming Pan & Yanrong Yang - 695-718 Control functionals for Monte Carlo integration
by Chris J. Oates & Mark Girolami & Nicolas Chopin - 719-735 Causal analysis of ordinal treatments and binary outcomes under truncation by death
by Linbo Wang & Thomas S. Richardson & Xiao-Hua Zhou - 737-756 Local explosion modelling by non-causal process
by Christian Gouriéroux & Jean-Michel Zakoïan - 757-777 Principal stratification analysis using principal scores
by Peng Ding & Jiannan Lu - 779-800 Additive model building for spatial regression
by Siddhartha Nandy & Chae Young Lim & Tapabrata Maiti - 801-813 Admissibility of the usual confidence set for the mean of a univariate or bivariate normal population: the unknown variance case
by Hannes Leeb & Paul Kabaila - 815-832 Regionalization of multiscale spatial processes by using a criterion for spatial aggregation error
by Jonathan R. Bradley & Christopher K. Wikle & Scott H. Holan - 833-857 Continuous auto-regressive moving average random fields on ℝ-super-n
by Peter J. Brockwell & Yasumasa Matsuda - 859-876 Optimal designs for longitudinal and functional data
by Hao Ji & Hans-Georg Müller - 877-897 Bayesian inference for Matérn repulsive processes
by Vinayak Rao & Ryan P. Adams & David D. Dunson - 899-916 Provable sparse tensor decomposition
by Will Wei Sun & Junwei Lu & Han Liu & Guang Cheng - 917-938 Mediation analysis with time varying exposures and mediators
by Tyler J. VanderWeele & Eric J. Tchetgen Tchetgen - 939-956 Linear and conic programming estimators in high dimensional errors-in-variables models
by Alexandre Belloni & Mathieu Rosenbaum & Alexandre B. Tsybakov
March 2017, Volume 79, Issue 2
- 323-380 A Bayesian information criterion for singular models
by Mathias Drton & Martyn Plummer - 381-404 Global envelope tests for spatial processes
by Mari Myllymäki & Tomáš Mrkvička & Pavel Grabarnik & Henri Seijo & Ute Hahn - 405-421 High dimensional semiparametric latent graphical model for mixed data
by Jianqing Fan & Han Liu & Yang Ning & Hui Zou - 423-448 Testing against a linear regression model using ideas from shape-restricted estimation
by Bodhisattva Sen & Mary Meyer - 449-461 Estimation of extreme depth-based quantile regions
by Yi He & John H. J. Einmahl - 463-482 Regression models on Riemannian symmetric spaces
by Emil Cornea & Hongtu Zhu & Peter Kim & Joseph G. Ibrahim - 483-505 Extending the Archimedean copula methodology to model multivariate survival data grouped in clusters of variable size
by Leen Prenen & Roel Braekers & Luc Duchateau - 507-524 Oracally efficient estimation and consistent model selection for auto-regressive moving average time series with trend
by Qin Shao & Lijian Yang - 525-545 Compound random measures and their use in Bayesian non-parametrics
by Jim E. Griffin & Fabrizio Leisen - 547-572 Probabilistic multi-resolution scanning for two-sample differences
by Jacopo Soriano & Li Ma - 573-587 Efficient estimation of semiparametric transformation models for the cumulative incidence of competing risks
by Lu Mao & D. Y. Lin - 589-611 Confidence intervals and regions for the lasso by using stochastic variational inequality techniques in optimization
by Shu Lu & Yufeng Liu & Liang Yin & Kai Zhang - 613-633 On the exact region determined by Kendall's τ and Spearman's ρ
by Manuela Schreyer & Roland Paulin & Wolfgang Trutschnig - 635-648 A frequentist approach to computer model calibration
by Raymond K. W. Wong & Curtis B. Storlie & Thomas C. M. Lee
January 2017, Volume 79, Issue 1
- 3-4 Report of the Editors—2016
by David Dunson & Piotr Fryzlewicz - 5-27 Classification of non-parametric regression functions in longitudinal data models
by Michael Vogt & Oliver Linton - 29-50 Detection of change in the spatiotemporal mean function
by Oleksandr Gromenko & Piotr Kokoszka & Matthew Reimherr - 51-67 On estimation of the noise variance in high dimensional probabilistic principal component analysis
by Damien Passemier & Zhaoyuan Li & Jianfeng Yao - 69-94 Laplace deconvolution on the basis of time domain data and its application to dynamic contrast-enhanced imaging
by Fabienne Comte & Charles-A. Cuenod & Marianna Pensky & Yves Rozenholc - 95-123 A test for stationarity for irregularly spaced spatial data
by Soutir Bandyopadhyay & Suhasini Subba Rao - 125-148 The normal law under linear restrictions: simulation and estimation via minimax tilting
by Z. I. Botev - 149-175 Modelling across extremal dependence classes
by J. L. Wadsworth & J. A. Tawn & A. C. Davison & D. M. Elton - 177-196 Modelling function-valued stochastic processes, with applications to fertility dynamics
by Kehui Chen & Pedro Delicado & Hans-Georg Müller - 197-223 Optimal screening and discovery of sparse signals with applications to multistage high throughput studies
by T. Tony Cai & Wenguang Sun - 225-246 Two-sample testing in high dimensions
by Nicolas Städler & Sach Mukherjee - 247-265 Estimation of high dimensional mean regression in the absence of symmetry and light tail assumptions
by Jianqing Fan & Quefeng Li & Yuyan Wang - 267-291 Fast moment-based estimation for hierarchical models
by Patrick O. Perry - 293-320 Hamiltonian Monte Carlo sampling in Bayesian empirical likelihood computation
by Sanjay Chaudhuri & Debashis Mondal & Teng Yin
November 2016, Volume 78, Issue 5
- 947-1012 Causal inference by using invariant prediction: identification and confidence intervals
by Jonas Peters & Peter Bühlmann & Nicolai Meinshausen - 1013-1035 Model checking for parametric single-index models: a dimension reduction model-adaptive approach
by Xu Guo & Tao Wang & Lixing Zhu - 1037-1055 Variable selection via additive conditional independence
by Kuang-Yao Lee & Bing Li & Hongyu Zhao - 1057-1078 Set estimation from reflected Brownian motion
by Alejandro Cholaquidis & Ricardo Fraiman & Gábor Lugosi & Beatriz Pateiro-López - 1079-1102 Tests for high dimensional generalized linear models
by Bin Guo & Song Xi Chen - 1103-1130 A general framework for updating belief distributions
by P. G. Bissiri & C. C. Holmes & S. G. Walker
September 2016, Volume 78, Issue 4
- 701-727 Mixtures, envelopes and hierarchical duality
by Nicholas G. Polson & James G. Scott - 729-754 Generalized additive and index models with shape constraints
by Yining Chen & Richard J. Samworth - 755-779 Double one-sided cross-validation of local linear hazards
by María Luz Gámiz & Enno Mammen & María Dolores Martínez Miranda & Jens Perch Nielsen - 781-804 Making the cut: improved ranking and selection for large-scale inference
by Nicholas C. Henderson & Michael A. Newton - 805-827 Robust inference in sample selection models
by Mikhail Zhelonkin & Marc G. Genton & Elvezio Ronchetti - 829-848 Principal causal effect identification and surrogate end point evaluation by multiple trials
by Zhichao Jiang & Peng Ding & Zhi Geng - 849-867 Distance shrinkage and Euclidean embedding via regularized kernel estimation
by Luwan Zhang & Grace Wahba & Ming Yuan - 869-893 Estimation of a two-component mixture model with applications to multiple testing
by Rohit Kumar Patra & Bodhisattva Sen - 895-916 Inference for multiple change points in time series via likelihood ratio scan statistics
by Chun Yip Yau & Zifeng Zhao - 917-931 Extensible grids: uniform sampling on a space filling curve
by Zhijian He & Art B. Owen - 933-946 Bayesian regularization of the length of memory in reversible sequences
by Sergio Bacallado & Vijay Pande & Stefano Favaro & Lorenzo Trippa
June 2016, Volume 78, Issue 3
- 505-562 Of quantiles and expectiles: consistent scoring functions, Choquet representations and forecast rankings
by Werner Ehm & Tilmann Gneiting & Alexander Jordan & Fabian Krüger - 563-587 Drift estimation in sparse sequential dynamic imaging, with application to nanoscale fluorescence microscopy
by Alexander Hartmann & Stephan Huckemann & Jörn Dannemann & Oskar Laitenberger & Claudia Geisler & Alexander Egner & Axel Munk - 589-611 High dimensional ordinary least squares projection for screening variables
by Xiangyu Wang & Chenlei Leng - 613-635 Estimating multivariate volatility models equation by equation
by Christian Francq & Jean-Michel Zakoïan - 637-653 Truncated linear models for functional data
by Peter Hall & Giles Hooker - 655-671 Randomization inference for treatment effect variation
by Peng Ding & Avi Feller & Luke Miratrix - 673-700 Globally efficient non-parametric inference of average treatment effects by empirical balancing calibration weighting
by Kwun Chuen Gary Chan & Sheung Chi Phillip Yam & Zheng Zhang
March 2016, Volume 78, Issue 2
- 319-341 Empirical likelihood confidence intervals for complex sampling designs
by Y. G. Berger & O. De La Riva Torres - 343-369 Simulation of multivariate diffusion bridges
by Mogens Bladt & Samuel Finch & Michael Sørensen - 371-394 Detecting relevant changes in time series models
by Holger Dette & Dominik Wied - 395-421 On the coverage bound problem of empirical likelihood methods for time series
by Xianyang Zhang & Xiaofeng Shao - 423-444 Sequential selection procedures and false discovery rate control
by Max Grazier G'Sell & Stefan Wager & Alexandra Chouldechova & Robert Tibshirani - 445-462 Making a non-parametric density estimator more attractive, and more accurate, by data perturbation
by Hassan Doosti & Peter Hall - 463-485 Bootstrapping the portmanteau tests in weak auto-regressive moving average models
by Ke Zhu - 487-504 Joint estimation of multiple graphical models from high dimensional time series
by Huitong Qiu & Fang Han & Han Liu & Brian Caffo
January 2016, Volume 78, Issue 1
- 3-30 Data envelope fitting with constrained polynomial splines
by Abdelaati Daouia & Hohsuk Noh & Byeong U. Park - 31-51 Statistics of heteroscedastic extremes
by John H. J. Einmahl & Laurens Haan & Chen Zhou - 53-76 Variable selection for support vector machines in moderately high dimensions
by Xiang Zhang & Yichao Wu & Lan Wang & Runze Li - 77-97 A tilting approach to ranking influence
by Marc G. Genton & Peter Hall - 99-126 Non-parametric inference for density modes
by Christopher R. Genovese & Marco Perone-Pacifico & Isabella Verdinelli & Larry Wasserman - 127-151 Semiparametric estimation in the secondary analysis of case–control studies
by Yanyuan Ma & Raymond J. Carroll - 153-174 Lasso regression: estimation and shrinkage via the limit of Gibbs sampling
by Bala Rajaratnam & Steven Roberts & Doug Sparks & Onkar Dalal - 175-191 Optimal designs for the prediction of individual parameters in hierarchical models
by Maryna Prus & Rainer Schwabe - 193-210 The lasso for high dimensional regression with a possible change point
by Sokbae Lee & Myung Hwan Seo & Youngki Shin - 211-229 Non-parametric estimation of finite mixtures from repeated measurements
by Stéphane Bonhomme & Koen Jochmans & Jean-Marc Robin - 231-252 Methodology for non-parametric deconvolution when the error distribution is unknown
by Aurore Delaigle & Peter Hall - 253-273 Hypothesis testing for automated community detection in networks
by Peter J. Bickel & Purnamrita Sarkar - 275-298 An M-estimator of spatial tail dependence
by John H. J. Einmahl & Anna Kiriliouk & Andrea Krajina & Johan Segers - 299-318 Using post-outcome measurement information in censoring-by-death problems
by Fan Yang & Dylan S. Small
November 2015, Volume 77, Issue 5
- 893-922 A new non-parametric stationarity test of time series in the time domain
by Lei Jin & Suojin Wang & Haiyan Wang