Computational Statistics & Data Analysis

1983 - 2025

Current editor(s): S.P. Azen

From Elsevier
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Volume 164, issue C, 2021

Projection-averaging-based cumulative covariance and its use in goodness-of-fit testing for single-index models

Kai Xu and Yeqing Zhou

Graph informed sliced inverse regression

Eugen Pircalabelu and Andreas Artemiou

Equivalence class selection of categorical graphical models

Federico Castelletti and Stefano Peluso

On efficient exact experimental designs for ordered treatments

Satya Prakash Singh and Ori Davidov

Semiparametric least-squares regression with doubly-censored data

Taehwa Choi, Arlene K.H. Kim and Sangbum Choi

Correlation for tree-shaped datasets and its Bayesian estimation

Shanjun Mao, Xiaodan Fan and Jie Hu

Outlier detection in networks with missing links

Solenne Gaucher, Olga Klopp and Geneviève Robin

A more powerful test of equality of high-dimensional two-sample means

Huaiyu Zhang and Haiyan Wang

Inference for partially observed epidemic dynamics guided by Kalman filtering techniques

Romain Narci, Maud Delattre, Catherine Larédo and Elisabeta Vergu

Volume 163, issue C, 2021

Two-sample high dimensional mean test based on prepivots

Santu Ghosh, Deepak Nag Ayyala and Rafael Hellebuyck

Feature filter for estimating central mean subspace and its sparse solution

Pei Wang, Xiangrong Yin, Qingcong Yuan and Richard Kryscio

Assessing dynamic effects on a Bayesian matrix-variate dynamic linear model: An application to task-based fMRI data analysis

Johnatan Cardona Jiménez and Carlos A. de B. Pereira

Multimodal Bayesian registration of noisy functions using Hamiltonian Monte Carlo

J. Derek Tucker, Lyndsay Shand and Kenny Chowdhary

Categorical CVA biplots

D.T. Rodwell, Carel van der Merwe and S. Gardner-Lubbe

Active set algorithms for estimating shape-constrained density ratios

Lutz Dümbgen, Alexandre Mösching and Christof Strähl

Covariate balancing functional propensity score for functional treatments in cross-sectional observational studies

Xiaoke Zhang, Wu Xue and Qiyue Wang

Volume 162, issue C, 2021

Bayesian subgroup analysis in regression using mixture models

Yunju Im and Aixin Tan

A motif building process for simulating random networks

Alan M. Polansky and Paramahansa Pramanik

Fast and scalable computations for Gaussian hierarchical models with intrinsic conditional autoregressive spatial random effects

Marco A.R. Ferreira, Erica M. Porter and Christopher T. Franck

Distributed one-step upgraded estimation for non-uniformly and non-randomly distributed data

Feifei Wang, Yingqiu Zhu, Danyang Huang, Haobo Qi and Hansheng Wang

Fitting jump additive models

Yicheng Kang, Yueyong Shi, Yuling Jiao, Wendong Li and Dongdong Xiang

Fast multivariate empirical cumulative distribution function with connection to kernel density estimation

Nicolas Langrené and Xavier Warin

Assessing the effective sample size for large spatial datasets: A block likelihood approach

Jonathan Acosta, Alfredo Alegría, Felipe Osorio and Ronny Vallejos

Volume 161, issue C, 2021

Testing error heterogeneity in censored linear regression

Caiyun Fan, Wenbin Lu and Yong Zhou

Bayes linear analysis for ordinary differential equations

Matthew Jones, Michael Goldstein, David Randell and Philip Jonathan

Copula Particle Filters

Carlos E. Rodríguez and Stephen G. Walker

Combining heterogeneous spatial datasets with process-based spatial fusion models: A unifying framework

Craig Wang and Reinhard Furrer

An ensemble of inverse moment estimators for sufficient dimension reduction

Qin Wang and Yuan Xue

A Bayesian semiparametric vector Multiplicative Error Model

Nicola Donelli, Stefano Peluso and Antonietta Mira

Testing the first-order separability hypothesis for spatio-temporal point patterns

Mohammad Ghorbani, Nafiseh Vafaei, Jiří Dvořák and Mari Myllymäki

Generalized accelerated hazards mixture cure models with interval-censored data

Xiaoyu Liu and Liming Xiang

A class of Birnbaum–Saunders type kernel density estimators for nonnegative data

Yoshihide Kakizawa

Fast Bayesian inference using Laplace approximations in nonparametric double additive location-scale models with right- and interval-censored data

Philippe Lambert

Communication-efficient distributed M-estimation with missing data

Jianwei Shi, Guoyou Qin, Huichen Zhu and Zhongyi Zhu

Harmless label noise and informative soft-labels in supervised classification

Daniel Ahfock and Geoffrey J. McLachlan

Bayesian multivariate latent class profile analysis: Exploring the developmental progression of youth depression and substance use

Jung Wun Lee, Hwan Chung and Saebom Jeon

Robust communication-efficient distributed composite quantile regression and variable selection for massive data

Kangning Wang, Shaomin Li and Benle Zhang

Volume 160, issue C, 2021

Two-sample test in high dimensions through random selection

Tao Qiu, Wangli Xu and Liping Zhu

FunCC: A new bi-clustering algorithm for functional data with misalignment

Marta Galvani, Agostino Torti, Alessandra Menafoglio and Simone Vantini

Robust tests for time series comparison based on Laplace periodograms

Lei Jin

Bias-corrected Kullback–Leibler distance criterion based model selection with covariables missing at random

Yuting Wei, Qihua Wang, Xiaogang Duan and Jing Qin

Robust distributed modal regression for massive data

Kangning Wang and Shaomin Li

Time stable empirical best predictors under a unit-level model

María Guadarrama, Domingo Morales and Isabel Molina

Frequentist delta-variance approximations with mixed-effects models and TMB

Nan Zheng and Noel Cadigan

Latent association graph inference for binary transaction data

David Reynolds and Luis Carvalho

Composite quantile regression for ultra-high dimensional semiparametric model averaging

Chaohui Guo, Jing Lv and Jibo Wu

Marginal false discovery rate for a penalized transformation survival model

Weijuan Liang, Shuangge Ma and Cunjie Lin

Parallel integrative learning for large-scale multi-response regression with incomplete outcomes

Ruipeng Dong, Daoji Li and Zemin Zheng

In the pursuit of sparseness: A new rank-preserving penalty for a finite mixture of factor analyzers

Nam-Hwui Kim and Ryan P. Browne

A kernel-based measure for conditional mean dependence

Tingyu Lai, Zhongzhan Zhang and Yafei Wang

Robust MAVE through nonconvex penalized regression

Jing Zhang, Qin Wang and D'Arcy Mays