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Content
July 2020, Volume 4, Issue 2
- 121-133 A selective overview of sparse sufficient dimension reduction
by Lu Li & Xuerong Meggie Wen & Zhou Yu - 134-134 Review of sparse sufficient dimension reduction: comment
by Liping Zhu - 135-145 Interval estimation for minimal clinically important difference and its classification error via a bootstrap scheme
by Zehua Zhou & Jiwei Zhao & Melissa Kluczynski - 146-148 Discussion on ‘Review of sparse sufficient dimension reduction’
by Xin Zhang - 149-150 Comment on ‘Review of sparse sufficient dimension reduction’
by Michael Declan Power & Yuexiao Dong - 151-151 Rejoinder on ‘A selective overview of sparse sufficient dimension reduction’
by Lu Li & Xuewong Meggie Wen & Zhou Yu - 152-160 Empirical likelihood estimation in multivariate mixture models with repeated measurements
by Yuejiao Fu & Yukun Liu & Hsiao-Hsuan Wang & Xiaogang Wang - 161-161 Discussion on ‘Review of sparse sufficient dimension reduction’
by Xin Chen - 162-171 Power-expected-posterior prior Bayes factor consistency for nested linear models with increasing dimensions
by D. Fouskakis & J. K. Innocent & L. Pericchi - 172-178 Efficient GMM estimation with singular system of moment conditions
by Zhiguo Xiao - 179-189 Forecasting semi-stationary processes and statistical arbitrage
by Si Bao & Shi Chen & Wei An Zheng & Yu Zhou - 190-201 A class of admissible estimators of multiple regression coefficient with an unknown variance
by Chengyuan Song & Dongchu Sun - 202-213 Quantile treatment effect estimation with dimension reduction
by Ying Zhang & Lei Wang & Menggang Yu & Jun Shao - 214-227 Optimal mean-variance reinsurance and investment strategy with constraints in a non-Markovian regime-switching model
by Liming Zhang & Rongming Wang & Jiaqin Wei - 228-229 The abstract of doctoral dissertation ‘Some research on hypothesis testing and nonparametric variable screening problems for high dimensional data’
by Yongshuai Chen & Hengjian Cui
July 2020, Volume 4, Issue 1
- 1-13 Optimal reinsurance designs based on risk measures: a review
by Jun Cai & Yichun Chi - 14-15 A discussion of ‘optimal reinsurance designs based on risk measures: a review’
by Tim J. Boonen - 16-19 Discussion on the paper ‘Optimal reinsurance design based on risk measures: a review’ by Yichun Chi and Jun Cai
by Chengguo Weng - 20-22 A hybrid model of optimal reinsurance: a discussion of ‘Optimal reinsurance designs based on risk measures: a review’ by Jun Cai and Yichun Chi
by Sheng Chao Zhuang - 23-25 Discussion of “optimal reinsurance designs based on risk measures: a review” by Jun Cai and Yichun Chi
by Ambrose Lo - 26-27 Responses to discussions on ‘Optimal reinsurance designs based on risk measures: a review’
by Jun Cai & Yichun Chi - 28-42 Model-based small area estimation with no samples within the areas, by benchmarking to marginal cross-sectional and time-series estimates
by Danny Pfeffermann & Michael Sverchkov & Richard Tiller & Lizhi Liu - 43-54 Group screening for ultra-high-dimensional feature under linear model
by Yong Niu & Riquan Zhang & Jicai Liu & Huapeng Li - 55-65 Convergence rate of principal component analysis with local-linear smoother for functional data under a unified weighing scheme
by Xingyu Yan & Xiaolong Pu & Yingchun Zhou & Xiaolei Xun - 66-77 Topic model for graph mining based on hierarchical Dirichlet process
by Haibin Zhang & Shang Huating & Xianyi Wu - 78-83 Power analysis, sample size calculation for testing the largest binomial probability
by Thuan Nguyen & Jiming Jiang - 84-96 Statistical arbitrage under the efficient market hypothesis
by Si Bao & Shi Chen & Xi Wang & Wei An Zheng & Yu Zhou - 97-108 Semiparametric estimation for accelerated failure time mixture cure model allowing non-curable competing risk
by Yijun Wang & Jiajia Zhang & Yincai Tang - 109-116 Meta-analysis of independent datasets using constrained generalised method of moments
by Menghao Xu & Jun Shao - 117-119 The abstract of doctoral dissertation ‘nonlinear wavelet density estimation and hazard rate estimation with data missing at random’
by Yuye Zou & Guoliang Fan & Riquan Zhang
July 2019, Volume 3, Issue 2
- 89-89 Editorial foreword, second issue, 2019
by Yang Cheng & Jun Shao - 90-102 Domain estimation under informative linkage
by Ray Chambers & Nicola Salvati & Enrico Fabrizi & Andrea Diniz da Silva - 103-113 On valid descriptive inference from non-probability sample
by Li-Chun Zhang - 114-128 Small area prediction of quantiles for zero-inflated data and an informative sample design
by Emily Berg & Danhyang Lee - 129-135 Small area estimation with subgroup analysis
by Xin Wang & Zhengyuan Zhu - 136-149 Multi-outcome longitudinal small area estimation – a case study
by Eric Slud & Yves Thibaudeau - 150-157 Generalised variance functions for longitudinal survey data
by Guoyi Zhang & Yang Cheng & Yan Lu - 158-169 Graph-based multivariate conditional autoregressive models
by Ye Liang - 170-177 A resampling approach to estimation of the linking variance in the Fay–Herriot model
by Snigdhansu Chatterjee - 178-185 Combining multiple imperfect data sources for small area estimation: a Bayesian model of provincial fertility rates in Cambodia
by Junni L. Zhang & John Bryant - 186-198 Improving timeliness and accuracy of estimates from the UK labour force survey
by D. J. Elliott & P. Zong - 199-207 An equivalence result for moment equations when data are missing at random
by Marian Hristache & Valentin Patilea - 208-212 Nearest neighbour imputation under single index models
by Jun Shao & Lei Wang - 213-223 Multivariate small area estimation under nonignorable nonresponse
by Danny Pfeffermann & Michael Sverchkov - 224-238 Using state space models as a statistical impact measurement of survey redesigns: a case study of the labour force survey of the Australian Bureau of Statistics
by Xichuan (Mark) Zhang & Jan A. van den Brakel & Siu-Ming Tam - 239-241 2019 International Workshop on Big Data and Modern Statistics held at ECNU, China
by Wei Zhao & Ying Zhang & Shanping Wang
January 2019, Volume 3, Issue 1
- 1-1 Editorial foreword
by Jun Shao & Dongchu Sun & Danyu Lin - 2-13 Prior-based Bayesian information criterion
by M. J. Bayarri & James O. Berger & Woncheol Jang & Surajit Ray & Luis R. Pericchi & Ingmar Visser - 14-16 A discussion of ‘prior-based Bayesian information criterion’
by Jiahua Chen & Zeny Feng - 17-18 A discussion of prior-based Bayesian information criterion (PBIC)
by Jiming Jiang & Thuan Nguyen - 19-21 A discussion of ‘prior-based Bayesian information criterion (PBIC)’
by Jun Shao & Sheng Zhang - 22-23 Discussion on prior-based Bayes information criterion
by Brunero Liseo - 24-25 Discussion of ‘Prior-based Bayesian Information Criterion (PBIC)’
by Sifan Liu & Dongchu Sun - 26-29 Discussion of ‘Prior-based Bayesian Information Criterion (PBIC)’
by Bertrand S. Clarke - 30-31 Discussion of ‘Prior-based Bayesian information criterion (PBIC)’
by Jan Hannig - 32-34 Discussion of prior-based Bayesian information criterion (PBIC) by M.J. Bayarria, James O. Berger, Woncheol Jang, Surajit Ray, Luis R. Pericchi, and Ingmar Visser
by Ryan A. Peterson & Joseph E. Cavanaugh - 35-36 Discussion on Prior-based Bayesian Information Criterion (PBIC) by M. J. Bayarri, James O. Berger, Woncheol Jang, Surajit Ray, Luis R. Pericchi, and Ingmar Visser
by Ruobin Gong & Minge Xie - 37-39 Rejoinder by James Berger, Woncheol Jang, Surajit Ray, Luis R. Pericchi and Ingmar Visser
by The Editors - 40-47 Measure of rotatability of modified five-level second-order rotatable design using supplementary difference sets
by Haron Mutai Ng’eno - 48-58 Development of a first order integrated moving average model corrupted with a Markov modulated convex combination of autoregressive moving average errors
by S. A. Komolafe & T. O. Obilade & I. O. Ayodeji & A. R. Babalola - 59-70 Some results on quantile-based Shannon doubly truncated entropy
by Vikas Kumar & Gulshan Taneja & Samsher Chhoker - 71-82 Shape-constrained semiparametric additive stochastic volatility models
by Jiangyong Yin & Peter F. Craigmile & Xinyi Xu & Steven MacEachern - 83-84 The appreciation of statistical thoughts
by Zhao Yujie - 85-88 Founding of the Big Data Statistics Branch
by Shanping Wang
July 2018, Volume 2, Issue 2
- 103-104 Editorial foreword, second issue, 2018
by Jun Shao & Dongchu Sun & Danyu Lin - 105-133 Statistical inference for nonignorable missing-data problems: a selective review
by Niansheng Tang & Yuanyuan Ju - 134-136 Variable screening with missing covariates: a discussion of ‘statistical inference for nonignorable missing data problems: a selective review’ by Niansheng Tang and Yuanyuan Ju
by Fang Fang & Lyu Ni - 137-139 Some issues on longitudinal data with nonignorable dropout, a discussion of “Statistical Inference for Nonignorable Missing-Data Problems: A Selective Review” by Niansheng Tang and Yuanyuan Ju
by Lei Wang - 140-140 A discussion of ‘statistical inference for nonignorable missing data problems: a selective review’ by Niansheng Tang and Yuanyuan Ju
by Kosuke Morikawa & Jae Kwang Kim - 141-142 Semiparametric propensity weighting for nonignorable nonresponse: a discussion of ‘Statistical inference for nonignorable missing data problems: a selective review’ by Niansheng Tang and Yuanyuan Ju
by Jun Shao - 143-145 Statistical methods without estimating the missingness mechanism: a discussion of ‘statistical inference for nonignorable missing data problems: a selective review’ by Niansheng Tang and Yuanyuan Ju
by Jiwei Zhao - 146-149 Rejoinder: statistical inference for non-ignorable missing-data problems: a selective review
by Niansheng Tang & Yuanyuan Ju - 150-157 Some results of classification problem by Bayesian method and application in credit operation
by Tai Vovan - 158-171 Combining estimators of a common parameter across samples
by Eric Slud & Ilia Vonta & Abram Kagan - 172-180 Efficient Robbins–Monro procedure for multivariate binary data
by Cui Xiong & Jin Xu - 181-195 Dynamic stress–strength reliability estimation of system with survival signature
by Yiming Liu & Yimin Shi & Xuchao Bai & Bin Liu - 196-205 Pseudo likelihood and dimension reduction for data with nonignorable nonresponse
by Ji Chen & Bingying Xie & Jun Shao - 206-214 The effects of additive outliers in INAR(1) process and robust estimation
by Marcelo Bourguignon & Klaus L. P. Vasconcellos - 215-218 Summaries of three keynote lectures at the SAE – 2018
by Kai Tan & Lyu Ni - 219-221 Interview with Professor Danny Pfeffermann
by Lyu Ni & Kai Tan - 222-224 How I became a statistician — thank you speech at birthday dinner
by Danny Pfeffermann
January 2018, Volume 2, Issue 1
- 1-1 Editorial foreword
by Jun Shao & Dongchu Sun & Danyu Lin - 2-10 Nutritional epidemiology methods and related statistical challenges and opportunities
by Ross L. Prentice & Ying Huang - 11-13 On the formation and use of calibration equations in nutritional epidemiology – Discussion of the Paper by R. L. Prentice and Y. Huang
by Laurence S. Freedman & Pamela A. Shaw - 14-20 Much room for optimism on measuring diet, preventing cancer and cardiovascular disease, and correcting for measurement error – discussion of the paper by R. L. Prentice and Y. Huang
by Donna Spiegelman - 21-22 Discussion of the paper by R. L. Prentice and Y. Huang: Optimal designs and efficient inference for biomarker studies
by D. Y. Lin - 23-26 Response to discussion of ‘Nutritional epidemiology methods and related statistical challenges and opportunities’
by Ross L. Prentice & Ying Huang - 27-36 Objective Bayesian analysis for the accelerated degradation model using Wiener process with measurement errors
by Daojiang He & Yunpeng Wang & Mingxiang Cao - 37-47 Objective Bayesian hypothesis testing and estimation for the intraclass model
by Duo Zhang & Daojiang He & Xiaoqian Sun & Tao Lu & Min Wang - 48-57 Statistical analysis of dependent competing risks model in constant stress accelerated life testing with progressive censoring based on copula function
by Xuchao Bai & Yimin Shi & Yiming Liu & Bin Liu - 58-67 Step-stress accelerated degradation test planning based on Wiener process with correlation
by Lei He & Rong-Xian Yue & Daojiang He - 68-79 A generalisation of the exponential distribution and its applications on modelling skewed data
by Muhammad Zubair & Ayman Alzaatreh & M. H. Tahir & Muhammad Mansoor & Manat Mustafa - 80-88 Deep advantage learning for optimal dynamic treatment regime
by Shuhan Liang & Wenbin Lu & Rui Song - 89-95 Impact of sufficient dimension reduction in nonparametric estimation of causal effect
by Ying Zhang & Jun Shao & Menggang Yu & Lei Wang - 96-101 Testing hypotheses under covariate-adaptive randomisation and additive models
by Ting Ye
July 2017, Volume 1, Issue 2
- 141-142 Second Issue, 2017
by Jun Shao & Dongchu Sun & Danyu Lin - 143-158 Multi-category diagnostic accuracy based on logistic regression
by Jialiang Li & Jason P. Fine & Michael J. Pencina - 159-170 Robust dynamic risk prediction with longitudinal studies
by Qian M. Zhou & Wei Dai & Yingye Zheng & Tianxi Cai - 171-181 Treatment recommendation and parameter estimation under single-index contrast function
by Cui Xiong & Menggang Yu & Jun Shao - 182-184 Personalised medicine with multiple treatments: a PhD thesis abstract
by Zhilan Lou - 185-193 Bayesian functional enrichment analysis for the Reactome database
by Jing Cao - 194-204 Semiparametric Bayesian analysis of high-dimensional censored outcome data
by Chetkar Jha & Yi Li & Subharup Guha - 205-215 The influence of misspecified covariance on false discovery control when using posterior probabilities
by Ye Liang & Joshua D. Habiger & Xiaoyi Min - 216-226 Statistical inference for zero-and-one-inflated poisson models
by Yincai Tang & Wenchen Liu & Ancha Xu - 227-233 Statistical estimation in partially nonlinear models with random effects
by Ye Que & Zhensheng Huang & Riquan Zhang - 234-245 Sequential profile Lasso for ultra-high-dimensional partially linear models
by Yujie Li & Gaorong Li & Tiejun Tong - 246-256 Factor analysis of correlation matrices when the number of random variables exceeds the sample size
by Miguel Marino & Yi Li - 257-264 Optimal AK composite estimators in current population survey
by Yang Cheng & Jun Shao & Zhou Yu - 265-266 Sample size calculations in clinical research, third edition, by Shein-Chung Chow, Jun Shao, Hansheng Wang, and Yuliya Lokhnygina
by Ting Ye & Yanyao Yi
January 2017, Volume 1, Issue 1
- 1-2 Editorial
by Jun Shao & Dongchu Sun & Danyu Lin - 3-14 Funnel testing in webpage optimisation: representation, design and analysis
by Heng Su & C. F. Jeff Wu - 15-27 On finite mixture models
by Jiahua Chen - 28-36 Achieving the oracle property of OEM with nonconvex penalties
by Shifeng Xiong & Bin Dai & Peter Z. G. Qian - 37-47 Personalised treatment assignment maximising expected benefit with smooth hinge loss
by Shixue Liu & Jun Shao & Menggang Yu - 48-58 Cholesky-based model averaging for covariance matrix estimation
by Hao Zheng & Kam-Wah Tsui & Xiaoning Kang & Xinwei Deng - 59-68 An adaptive lack of fit test for big data
by Yanyan Zhao & Changliang Zou & Zhaojun Wang - 69-81 Semiparametric fractional imputation using empirical likelihood in survey sampling
by Sixia Chen & Jae kwang Kim - 82-91 Quasi-Monte Carlo simulation of Brownian sheet with application to option pricing
by Xinyu Song & Yazhen Wang - 92-111 An extended sparse max-linear moving model with application to high-frequency financial data
by Timothy Idowu & Zhengjun Zhang - 112-120 Portfolio optimisation using constrained hierarchical bayes models
by Jiangyong Yin & Xinyi Xu - 121-127 Power analysis for stratified cluster randomisation trials with cluster size being the stratifying factor
by Jijia Wang & Song Zhang & Chul Ahn - 128-140 Bayesian analysis of series system with dependent causes of failure
by Ancha Xu & Shirong Zhou