Computational Statistics & Data Analysis

1983 - 2018

Current editor(s): S.P. Azen

From Elsevier
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Volume 126, issue C, 2018

A particle-learning-based approach to estimate the influence matrix of online social networks pp. 1-18

Luis E. Castro and Nazrul I. Shaikh

Small area estimation under a spatially non-linear model pp. 19-38

Hukum Chandra, Nicola Salvati and Ray Chambers

Sensible functional linear discriminant analysis pp. 39-52

Lu-Hung Chen and Ci-Ren Jiang

Recalibration: A post-processing method for approximate Bayesian computation pp. 53-66

G.S. Rodrigues, D. Prangle and S.A. Sisson

On sufficient dimension reduction with missing responses through estimating equations pp. 67-77

Yuexiao Dong, Qi Xia, Cheng Yong Tang and Zeda Li

Balanced estimation for high-dimensional measurement error models pp. 78-91

Zemin Zheng, Yang Li, Chongxiu Yu and Gaorong Li

Bayesian quantile regression using the skew exponential power distribution pp. 92-111

Mauro Bernardi, Marco Bottone and Lea Petrella

An induced natural selection heuristic for finding optimal Bayesian experimental designs pp. 112-124

David J. Price, Nigel G. Bean, Joshua V. Ross and Jonathan Tuke

Sparse pathway-based prediction models for high-throughput molecular data pp. 125-135

Sangin Lee, Youngjo Lee and Yudi Pawitan

Bayesian inference on group differences in multivariate categorical data pp. 136-149

Massimiliano Russo, Daniele Durante and Bruno Scarpa

A Bayesian data combination approach for repeated durations under unobserved missing indicators: Application to interpurchase-timing in marketing pp. 150-166

Ryosuke Igari and Takahiro Hoshino

Volume 125, issue C, 2018

Semiparametric analysis of the additive hazards model with informatively interval-censored failure time data pp. 1-9

Shuying Wang, Chunjie Wang, Peijie Wang and Jianguo Sun

Robust template estimation for functional data with phase variability using band depth pp. 10-26

Jason Cleveland, Weilong Zhao and Wei Wu

Continuum directions for supervised dimension reduction pp. 27-43

Sungkyu Jung

Unsupervised learning of mixture regression models for longitudinal data pp. 44-56

Peirong Xu, Heng Peng and Tao Huang

A scale space approach for exploring structure in spherical data pp. 57-69

Ville Vuollo and Lasse Holmström

Identifying outliers using multiple kernel canonical correlation analysis with application to imaging genetics pp. 70-85

Md. Ashad Alam, Vince D. Calhoun and Yu-Ping Wang

Point process models for novelty detection on spatial point patterns and their extremes pp. 86-103

Stijn E. Luca, Marco A.F. Pimentel, Peter J. Watkinson and David A. Clifton

On the sample mean after a group sequential trial pp. 104-118

Ben Berckmoes, Anna Ivanova and Geert Molenberghs

Identification of local sparsity and variable selection for varying coefficient additive hazards models pp. 119-135

Lianqiang Qu, Xinyuan Song and Liuquan Sun

Supervised dimension reduction for ordinal predictors pp. 136-155

Liliana Forzani, Rodrigo García Arancibia, Pamela Llop and Diego Tomassi

Joint regression analysis of mixed-type outcome data via efficient scores pp. 156-170

Scott Marchese and Guoqing Diao

Volume 124, issue C, 2018

Multivariate specification tests based on a dynamic Rosenblatt transform pp. 1-14

Igor L. Kheifets

Testing the equality of several covariance functions for functional data: A supremum-norm based test pp. 15-26

Jia Guo, Bu Zhou and Jin-Ting Zhang

On constrained estimation of graphical time series models pp. 27-52

T.P. Yuen, H. Wong and K.F.C. Yiu

Semiparametric regression analysis of clustered survival data with semi-competing risks pp. 53-70

Mengjiao Peng, Liming Xiang and Shanshan Wang

Multilevel rejection sampling for approximate Bayesian computation pp. 71-86

David J. Warne, Ruth E. Baker and Matthew J. Simpson

A family of the information criteria using the phi-divergence for categorical data pp. 87-103

Haruhiko Ogasawara

Penalized composite likelihoods for inhomogeneous Gibbs point process models pp. 104-116

Jeffrey Daniel, Julie Horrocks and Gary J. Umphrey

Bootstrapping longitudinal data with multiple levels of variation pp. 117-131

O’Shaughnessy, P.Y. and A.H. Welsh

Variable selection for high dimensional Gaussian copula regression model: An adaptive hypothesis testing procedure pp. 132-150

Yong He, Xinsheng Zhang and Liwen Zhang

Fast Bayesian inference using Laplace approximations in a flexible promotion time cure model based on P-splines pp. 151-167

Oswaldo Gressani and Philippe Lambert

Response-adaptive treatment allocation for non-inferiority trials with heterogeneous variances pp. 168-179

Wenfu Xu, Jingya Gao, Feifang Hu and Siu Hung Cheung

Sparse principal component regression for generalized linear models pp. 180-196

Shuichi Kawano, Hironori Fujisawa, Toyoyuki Takada and Toshihiko Shiroishi

Objective priors for the number of degrees of freedom of a multivariate t distribution and the t-copula pp. 197-219

Cristiano Villa and Francisco J. Rubio

Overfitting Bayesian mixtures of factor analyzers with an unknown number of components pp. 220-234

Panagiotis Papastamoulis

A Forward and Backward Stagewise algorithm for nonconvex loss functions with adaptive Lasso pp. 235-251

Xingjie Shi, Yuan Huang, Jian Huang and Shuangge Ma

Optimal projection of observations in a Bayesian setting pp. 252-276

Loïc Giraldi, Olivier P. Le Maître, Ibrahim Hoteit and Omar M. Knio

Optimal Bayesian design for discriminating between models with intractable likelihoods in epidemiology pp. 277-297

Mahasen B. Dehideniya, Christopher C. Drovandi and James M. McGree

Volume 123, issue C, 2018

Depth-weighted Bayes classification pp. 1-12

Ondrej Vencalek and Oleksii Pokotylo

Approximation error approach in spatiotemporally chaotic models with application to Kuramoto–Sivashinsky equation pp. 13-31

J.M.J. Huttunen, J.P. Kaipio and H. Haario

Clustering sparse binary data with hierarchical Bayesian Bernoulli mixture model pp. 32-49

Mao Ye, Peng Zhang and Lizhen Nie

Time-dynamic varying coefficient models for longitudinal data pp. 50-65

Kyeongeun Lee, Young K. Lee, Byeong U. Park and Seong J. Yang

Compositional regression with functional response pp. 66-85

R. Talská, A. Menafoglio, J. Machalová, K. Hron and E. Fišerová

Dealing with reciprocity in dynamic stochastic block models pp. 86-100

Francesco Bartolucci, Maria Francesca Marino and Silvia Pandolfi

Model-based co-clustering for ordinal data pp. 101-115

Julien Jacques and Christophe Biernacki

A sparse linear algebra algorithm for fast computation of prediction variances with Gaussian Markov random fields pp. 116-130

Andrew Zammit-Mangion and Jonathan Rougier

Likelihood based inference for the multivariate renewal Hawkes process pp. 131-145

Tom Stindl and Feng Chen

Semiparametric spatial model for interval-censored data with time-varying covariate effects pp. 146-156

Yue Zhang and Bin Zhang

Volume 122, issue C, 2018

Optimal exact tests for multiple binary endpoints pp. 1-17

Robin Ristl, Dong Xi, Ekkehard Glimm and Martin Posch

Fused mean–variance filter for feature screening pp. 18-32

Xiaodong Yan, Niansheng Tang, Jinhan Xie, Xianwen Ding and Zhiqiang Wang

Model selection for time series of count data pp. 33-44

Naif Alzahrani, Peter Neal, Simon E.F. Spencer, Trevelyan J. McKinley and Panayiota Touloupou

Flexible and efficient estimating equations for variogram estimation pp. 45-58

Ying Sun, Xiaohui Chang and Yongtao Guan

Analysis of generalized semiparametric regression models for cumulative incidence functions with missing covariates pp. 59-79

Unkyung Lee, Yanqing Sun, Thomas H. Scheike and Peter B. Gilbert

Approximate nonparametric maximum likelihood for mixture models: A convex optimization approach to fitting arbitrary multivariate mixing distributions pp. 80-91

Long Feng and Lee H. Dicker

A simple and fast method for computing the Poisson binomial distribution function pp. 92-100

William Biscarri, Sihai Dave Zhao and Robert J. Brunner

A joint design for functional data with application to scheduling ultrasound scans pp. 101-114

So Young Park, Luo Xiao, Jayson D. Willbur, Ana-Maria Staicu and Jumbe, N. L’ntshotsholé

Bayesian inference for conditional copulas using Gaussian Process single index models pp. 115-134

Evgeny Levi and Radu V. Craiu

Goodness-of-fit test for nonparametric regression models: Smoothing spline ANOVA models as example pp. 135-155

Sebastian J. Teran Hidalgo, Michael C. Wu, Stephanie M. Engel and Michael R. Kosorok

Group testing case identification with biomarker information pp. 156-166

Dewei Wang, Christopher S. McMahan, Joshua M. Tebbs and Christopher R. Bilder