Computational Statistics & Data Analysis

1983 - 2025

Current editor(s): S.P. Azen

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Volume 71, issue C, 2014

Model based clustering of customer choice data pp. 3-13

Donatella Vicari and Marco Alfó

Clustering longitudinal profiles using P-splines and mixed effects models applied to time-course gene expression data pp. 14-29

N. Coffey, J. Hinde and E. Holian

A new semi-parametric mixture model for interval censored data, with applications in the field of antimicrobial resistance pp. 30-42

Stijn Jaspers, Marc Aerts, Geert Verbeke and Pierre-Alexandre Beloeil

Mixture models for clustering multilevel growth trajectories pp. 43-51

S.K. Ng and G.J. McLachlan

Model-based clustering of high-dimensional data: A review pp. 52-78

Charles Bouveyron and Camille Brunet-Saumard

A hierarchical modeling approach for clustering probability density functions pp. 79-91

Daniela G. Calò, Angela Montanari and Cinzia Viroli

Model-based clustering for multivariate functional data pp. 92-106

Julien Jacques and Cristian Preda

A combined likelihood ratio/information ratio bootstrap technique for estimating the number of components in finite mixtures pp. 107-115

Athanase Polymenis

Robust mixture regression using the t-distribution pp. 116-127

Weixin Yao, Yan Wei and Chun Yu

Robust mixture regression model fitting by Laplace distribution pp. 128-137

Weixing Song, Weixin Yao and Yanru Xing

A multivariate linear regression analysis using finite mixtures of t distributions pp. 138-150

Giuliano Galimberti and Gabriele Soffritti

Zero-inflated Poisson regression mixture model pp. 151-158

Hwa Kyung Lim, Wai Keung Li and Philip L.H. Yu

Model-based clustering via linear cluster-weighted models pp. 159-182

Salvatore Ingrassia, Simona C. Minotti and Antonio Punzo

Learning from incomplete data via parameterized t mixture models through eigenvalue decomposition pp. 183-195

Tsung-I Lin

Parsimonious skew mixture models for model-based clustering and classification pp. 196-210

Irene Vrbik and Paul D. McNicholas

Nonparametric estimation of the mixing distribution in logistic regression mixed models with random intercepts and slopes pp. 211-219

Mary Lesperance, Rabih Saab and John Neuhaus

Robust growth mixture models with non-ignorable missingness: Models, estimation, selection, and application pp. 220-240

Lu, Zhenqiu (Laura) and Zhiyong Zhang

Multivariate methods using mixtures: Correspondence analysis, scaling and pattern-detection pp. 241-261

Shirley Pledger and Richard Arnold

Mixtures of equispaced normal distributions and their use for testing symmetry with univariate data pp. 262-272

Silvia Bacci and Francesco Bartolucci

State space mixed models for binary responses with scale mixture of normal distributions links pp. 274-287

Carlos A. Abanto-Valle and Dipak K. Dey

Optimal sequential designs in phase I studies pp. 288-297

David Azriel

Bayesian forecasting with small and medium scale factor-augmented vector autoregressive DSGE models pp. 298-323

Stelios Bekiros and Alessia Paccagnini

A hierarchical Bayes model for biomarker subset effects in clinical trials pp. 324-334

Bingshu E. Chen, Wenyu Jiang and Dongsheng Tu

Bayesian nonparametric k-sample tests for censored and uncensored data pp. 335-346

Yuhui Chen and Timothy E. Hanson

Fast Bayesian model assessment for nonparametric additive regression pp. 347-358

S. McKay Curtis, Sayantan Banerjee and Subhashis Ghosal

Characterising economic trends by Bayesian stochastic model specification search pp. 359-374

Stefano Grassi and Tommaso Proietti

An evolutionary Monte Carlo algorithm for Bayesian block clustering of data matrices pp. 375-391

Mayetri Gupta

Computation of marginal likelihoods with data-dependent support for latent variables pp. 392-401

Sarah E. Heaps, Richard J. Boys and Malcolm Farrow

Use of SAMC for Bayesian analysis of statistical models with intractable normalizing constants pp. 402-416

Ick Hoon Jin and Faming Liang

Dependent mixture models: Clustering and borrowing information pp. 417-433

Antonio Lijoi, Bernardo Nipoti and Igor Prünster

Simulation-based Bayesian inference for epidemic models pp. 434-447

Trevelyan J. McKinley, Joshua V. Ross, Rob Deardon and Alex R. Cook

Prior adjusted default Bayes factors for testing (in)equality constrained hypotheses pp. 448-463

Joris Mulder

Bayesian binary regression with exponential power link pp. 464-476

L. Naranjo, J. Martín and C.J. Pérez

Bayesian semiparametric analysis of short- and long-term hazard ratios with covariates pp. 477-490

Luis E. Nieto-Barajas

Mixtures of experts for understanding model discrepancy in dynamic computer models pp. 491-505

David J. Nott, Lucy Marshall, Mark Fielding and Shie-Yui Liong

A Bayesian model for longitudinal circular data based on the projected normal distribution pp. 506-519

Gabriel Nuñez-Antonio and Eduardo Gutiérrez-Peña

One-sample Bayes inference for symmetric distributions of 3-D rotations pp. 520-529

Yu Qiu, Daniel J. Nordman and Stephen B. Vardeman

Bayesian analysis of a Gibbs hard-core point pattern model with varying repulsion range pp. 530-541

T. Rajala and A. Penttinen

Bayesian Dirichlet mixture model for multivariate extremes: A re-parametrization pp. 542-567

Anne Sabourin and Philippe Naveau

Bayesian analysis of tail asymmetry based on a threshold extreme value model pp. 568-587

Mike K.P. So and Raymond K.S. Chan

Incorporation of gene exchangeabilities improves the reproducibility of gene set rankings pp. 588-598

Charlotte Soneson and Magnus Fontes

Modelling species abundance in a river by Negative Binomial hidden Markov models pp. 599-614

L. Spezia, S.L. Cooksley, M.J. Brewer, D. Donnelly and A. Tree

Reversible jump MCMC for nonparametric drift estimation for diffusion processes pp. 615-632

Frank van der Meulen, Moritz Schauer and Harry van Zanten

Linear Bayes estimator for the two-parameter exponential family under type II censoring pp. 633-642

Lichun Wang and Radhey S. Singh

GPU accelerated MCMC for modeling terrorist activity pp. 643-651

Gentry White and Michael D. Porter

Hypercube estimators: Penalized least squares, submodel selection, and numerical stability pp. 654-666

Rudolf Beran

Data mining for longitudinal data under multicollinearity and time dependence using penalized generalized estimating equations pp. 667-680

A. Blommaert, N. Hens and Ph. Beutels

Analysis of feature selection stability on high dimension and small sample data pp. 681-693

David Dernoncourt, Blaise Hanczar and Jean-Daniel Zucker

On selecting interacting features from high-dimensional data pp. 694-708

Peter Hall and Jing-Hao Xue

Linear instrumental variables model averaging estimation pp. 709-724

Luis Martins and Vasco Gabriel

Using random subspace method for prediction and variable importance assessment in linear regression pp. 725-742

Jan Mielniczuk and Paweł Teisseyre

LOL selection in high dimension pp. 743-757

M. Mougeot, D. Picard and K. Tribouley

Model selection and model averaging after multiple imputation pp. 758-770

Michael Schomaker and Christian Heumann

Sparse group lasso and high dimensional multinomial classification pp. 771-786

Martin Vincent and Niels Richard Hansen

Classification with decision trees from a nonparametric predictive inference perspective pp. 789-802

Joaquín Abellán, Rebecca M. Baker, Frank P.A. Coolen, Richard J. Crossman and Andrés R. Masegosa

Bootstrap confidence sets for the Aumann mean of a random closed set pp. 803-817

Christine Choirat and Raffaello Seri

Credal ensembles of classifiers pp. 818-831

G. Corani and A. Antonucci

Estimating mutual information for feature selection in the presence of label noise pp. 832-848

Benoît Frénay, Gauthier Doquire and Michel Verleysen

Computational issues of generalized fiducial inference pp. 849-858

Jan Hannig, Randy C.S. Lai and Thomas C.M. Lee

Optimal experimental designs for partial likelihood information pp. 859-867

J. López-Fidalgo and M.J. Rivas-López

Stochastic dominance with imprecise information pp. 868-886

Ignacio Montes, Enrique Miranda and Susana Montes

Reduced-rank vector generalized linear models with two linear predictors pp. 889-902

Thomas W. Yee

Transform both sides model: A parametric approach pp. 903-913

A. Polpo, C.P. de Campos, D. Sinha, S. Lipsitz and J. Lin

Maximum likelihood estimation of spatially and serially correlated panels with random effects pp. 914-933

Giovanni Millo

Basic Singular Spectrum Analysis and forecasting with R pp. 934-954

Nina Golyandina and Anton Korobeynikov

Parameter estimation for the 4-parameter Asymmetric Exponential Power distribution by the method of L-moments using R pp. 955-970

William H. Asquith

MultiLCIRT: An R package for multidimensional latent class item response models pp. 971-985

Francesco Bartolucci, Silvia Bacci and Michela Gnaldi

(Psycho-)analysis of benchmark experiments: A formal framework for investigating the relationship between data sets and learning algorithms pp. 986-1000

Manuel J.A. Eugster, Friedrich Leisch and Carolin Strobl

Discretization-based direct random sample generation pp. 1001-1010

Liqun Wang and Chel Hee Lee

Generating beta random numbers and Dirichlet random vectors in R: The package rBeta2009 pp. 1011-1020

Ching-Wei Cheng, Ying-Chao Hung and Narayanaswamy Balakrishnan

KrigInv: An efficient and user-friendly implementation of batch-sequential inversion strategies based on kriging pp. 1021-1034

Clément Chevalier, Victor Picheny and David Ginsbourger

Noisy kriging-based optimization methods: A unified implementation within the DiceOptim package pp. 1035-1053

Victor Picheny and David Ginsbourger

RcppArmadillo: Accelerating R with high-performance C++ linear algebra pp. 1054-1063

Dirk Eddelbuettel and Conrad Sanderson

Bayesian D-optimal designs for the two parameter logistic mixed effects model pp. 1066-1076

Haftom T. Abebe, Frans E.S. Tan, Gerard J.P. Van Breukelen and Martijn P.F. Berger

Experimental designs for drug combination studies pp. 1077-1087

B. Almohaimeed and A.N. Donev

Optimal design for correlated processes with input-dependent noise pp. 1088-1102

A. Boukouvalas, D. Cornford and M. Stehlík

‘Nearly’ universally optimal designs for models with correlated observations pp. 1103-1112

Holger Dette, Andrey Pepelyshev and Anatoly Zhigljavsky

Algorithms for approximate linear regression design with application to a first order model with heteroscedasticity pp. 1113-1123

N. Gaffke, U. Graßhoff and R. Schwabe

A class of composite designs for response surface methodology pp. 1124-1133

Stelios D. Georgiou, Stella Stylianou and Manohar Aggarwal

An efficient procedure for the avoidance of disconnected incomplete block designs pp. 1134-1146

J.D. Godolphin and H.R. Warren

Augmenting supersaturated designs with Bayesian D-optimality pp. 1147-1158

Alex J. Gutman, Edward D. White, Dennis K.J. Lin and Raymond R. Hill

Computing efficient exact designs of experiments using integer quadratic programming pp. 1159-1167

Radoslav Harman and Lenka Filová

Construction of experimental designs for estimating variance components pp. 1168-1177

S. Loeza-Serrano and A.N. Donev

Optimal designed experiments using a Pareto front search for focused preference of multiple objectives pp. 1178-1192

Lu Lu, Christine M. Anderson-Cook and Dennis K.J. Lin

A coordinate-exchange two-phase local search algorithm for the D- and I-optimal designs of split-plot experiments pp. 1193-1207

Francesco Sambo, Matteo Borrotti and Kalliopi Mylona

Integral approximations for computing optimum designs in random effects logistic regression models pp. 1208-1220

C. Tommasi, J.M. Rodríguez-Díaz and M.T. Santos-Martín