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ORCIDComputational Statistics & Data Analysis, Volume 71
Volume 71, March 2014
- Dankmar Böhning, Christian Hennig, Geoffrey J. McLachlan, Paul D. McNicholas
:
The 2nd special issue on advances in mixture models. 1-2
- Donatella Vicari, Marco Alfò:
Model based clustering of customer choice data. 3-13 - Norma Bargary, John Hinde, E. Holian:
Clustering longitudinal profiles using P-splines and mixed effects models applied to time-course gene expression data. 14-29 - Stijn Jaspers, Marc Aerts, Geert Verbeke, Pierre-Alexandre Beloeil:
A new semi-parametric mixture model for interval censored data, with applications in the field of antimicrobial resistance. 30-42 - Shu-Kay Ng, Geoffrey J. McLachlan:
Mixture models for clustering multilevel growth trajectories. 43-51 - Charles Bouveyron, Camille Brunet-Saumard:
Model-based clustering of high-dimensional data: A review. 52-78 - Daniela G. Calò, Angela Montanari, Cinzia Viroli:
A hierarchical modeling approach for clustering probability density functions. 79-91 - Julien Jacques, Cristian Preda:
Model-based clustering for multivariate functional data. 92-106 - Athanase Polymenis:
A combined likelihood ratio/information ratio bootstrap technique for estimating the number of components in finite mixtures. 107-115 - Weixin Yao, Yan Wei, Chun Yu:
Robust mixture regression using the t-distribution. 116-127 - Weixing Song, Weixin Yao, Yanru Xing:
Robust mixture regression model fitting by Laplace distribution. 128-137 - Giuliano Galimberti, Gabriele Soffritti:
A multivariate linear regression analysis using finite mixtures of t distributions. 138-150 - Hwa Kyung Lim, Wai Keung Li, Philip L. H. Yu:
Zero-inflated Poisson regression mixture model. 151-158 - Salvatore Ingrassia, Simona C. Minotti, Antonio Punzo:
Model-based clustering via linear cluster-weighted models. 159-182 - Tsung-I Lin:
Learning from incomplete data via parameterized t mixture models through eigenvalue decomposition. 183-195 - Irene Vrbik, Paul D. McNicholas:
Parsimonious skew mixture models for model-based clustering and classification. 196-210 - Mary Lesperance, Rabih Saab, John Neuhaus:
Nonparametric estimation of the mixing distribution in logistic regression mixed models with random intercepts and slopes. 211-219 - Zhenqiu (Laura) Lu, Zhiyong Zhang:
Robust growth mixture models with non-ignorable missingness: Models, estimation, selection, and application. 220-240 - Shirley Pledger, Richard Arnold:
Multivariate methods using mixtures: Correspondence analysis, scaling and pattern-detection. 241-261 - Silvia Bacci, Francesco Bartolucci:
Mixtures of equispaced normal distributions and their use for testing symmetry with univariate data. 262-272
- Cathy W. S. Chen, David B. Dunson, Sylvia Frühwirth-Schnatter, Stephen G. Walker:
Special issue on Bayesian computing, methods and applications. 273
- Carlos A. Abanto-Valle, Dipak K. Dey:
State space mixed models for binary responses with scale mixture of normal distributions links. 274-287 - David Azriel:
Optimal sequential designs in phase I studies. 288-297 - Stelios D. Bekiros, Alessia Paccagnini:
Bayesian forecasting with small and medium scale factor-augmented vector autoregressive DSGE models. 298-323 - Bingshu E. Chen, Wenyu Jiang, Dongsheng Tu:
A hierarchical Bayes model for biomarker subset effects in clinical trials. 324-334 - Yuhui Chen, Timothy E. Hanson:
Bayesian nonparametric k-sample tests for censored and uncensored data. 335-346 - S. McKay Curtis, Sayantan Banerjee, Subhashis Ghosal:
Fast Bayesian model assessment for nonparametric additive regression. 347-358 - Stefano Grassi, Tommaso Proietti:
Characterising economic trends by Bayesian stochastic model specification search. 359-374 - Mayetri Gupta:
An evolutionary Monte Carlo algorithm for Bayesian block clustering of data matrices. 375-391 - Sarah E. Heaps, Richard J. Boys, Malcolm Farrow:
Computation of marginal likelihoods with data-dependent support for latent variables. 392-401 - Ick-Hoon Jin, Faming Liang:
Use of SAMC for Bayesian analysis of statistical models with intractable normalizing constants. 402-416 - Antonio Lijoi, Bernardo Nipoti, Igor Prünster:
Dependent mixture models: Clustering and borrowing information. 417-433 - Trevelyan J. McKinley, Joshua V. Ross, Rob Deardon, Alex R. Cook:
Simulation-based Bayesian inference for epidemic models. 434-447 - Joris Mulder:
Prior adjusted default Bayes factors for testing (in)equality constrained hypotheses. 448-463 - Lizbeth Naranjo, Jacinto Martín, Carlos J. Pérez:
Bayesian binary regression with exponential power link. 464-476 - Luis E. Nieto-Barajas:
Bayesian semiparametric analysis of short- and long-term hazard ratios with covariates. 477-490 - David J. Nott, Lucy A. Marshall, Mark Fielding, Shie-Yui Liong:
Mixtures of experts for understanding model discrepancy in dynamic computer models. 491-505 - Gabriel Nuñez-Antonio, Eduardo Gutiérrez-Peña:
A Bayesian model for longitudinal circular data based on the projected normal distribution. 506-519 - Yu Qiu, Daniel J. Nordman, Stephen B. Vardeman:
One-sample Bayes inference for symmetric distributions of 3-D rotations. 520-529 - Tuomas Rajala, Antti Penttinen:
Bayesian analysis of a Gibbs hard-core point pattern model with varying repulsion range. 530-541 - Anne Sabourin, Philippe Naveau:
Bayesian Dirichlet mixture model for multivariate extremes: A re-parametrization. 542-567 - Mike K. P. So, Raymond K. S. Chan:
Bayesian analysis of tail asymmetry based on a threshold extreme value model. 568-587 - Charlotte Soneson, Magnus Fontes:
Incorporation of gene exchangeabilities improves the reproducibility of gene set rankings. 588-598 - Luigi Spezia, S. L. Cooksley, M. J. Brewer, D. Donnelly, A. Tree:
Modelling species abundance in a river by Negative Binomial hidden Markov models. 599-614 - Frank van der Meulen, Moritz Schauer, Harry van Zanten:
Reversible jump MCMC for nonparametric drift estimation for diffusion processes. 615-632 - Lichun Wang, Radhey S. Singh:
Linear Bayes estimator for the two-parameter exponential family under type II censoring. 633-642 - Gentry White, Michael D. Porter:
GPU accelerated MCMC for modeling terrorist activity. 643-651
- S. Ejaz Ahmed, Gerda Claeskens, Hidetoshi Shimodaira, Stefan Van Aelst:
Special issue on Model Selection and High Dimensional Data Reduction. 652-653
- Rudolf Beran:
Hypercube estimators: Penalized least squares, submodel selection, and numerical stability. 654-666 - A. Blommaert, Niel Hens, Philippe Beutels:
Data mining for longitudinal data under multicollinearity and time dependence using penalized generalized estimating equations. 667-680 - David Dernoncourt, Blaise Hanczar, Jean-Daniel Zucker:
Analysis of feature selection stability on high dimension and small sample data. 681-693 - Peter Hall, Jing-Hao Xue:
On selecting interacting features from high-dimensional data. 694-708 - Luís F. Martins, Vasco J. Gabriel:
Linear instrumental variables model averaging estimation. 709-724 - Jan Mielniczuk, Pawel Teisseyre:
Using random subspace method for prediction and variable importance assessment in linear regression. 725-742 - Mathilde Mougeot, Dominique Picard, Karine Tribouley:
LOL selection in high dimension. 743-757 - Michael Schomaker, Christian Heumann:
Model selection and model averaging after multiple imputation. 758-770 - Martin Vincent, Niels Richard Hansen:
Sparse group lasso and high dimensional multinomial classification. 771-786
- Ana Colubi, Thierry Denoeux:
Special issue on imprecision in statistical data analysis. 787-788
- Joaquín Abellán, Rebecca M. Baker, Frank P. A. Coolen, Richard J. Crossman, Andrés R. Masegosa:
Classification with decision trees from a nonparametric predictive inference perspective. 789-802 - Christine Choirat, Raffaello Seri:
Bootstrap confidence sets for the Aumann mean of a random closed set. 803-817 - Giorgio Corani, Alessandro Antonucci:
Credal ensembles of classifiers. 818-831 - Benoît Frénay, Gauthier Doquire, Michel Verleysen:
Estimating mutual information for feature selection in the presence of label noise. 832-848 - Jan Hannig, Randy C. S. Lai, Thomas C. M. Lee:
Computational issues of generalized fiducial inference. 849-858 - Jesús López-Fidalgo, María Jesús Rivas-López:
Optimal experimental designs for partial likelihood information. 859-867 - Ignacio Montes, Enrique Miranda, Susana Montes:
Stochastic dominance with imprecise information. 868-886
- Peter Filzmoser, Cristian Gatu, Achim Zeileis:
Special issue on statistical algorithms and software in R. 887-888
- Thomas W. Yee:
Reduced-rank vector generalized linear models with two linear predictors. 889-902 - Adriano Polpo, Cassio P. de Campos, Debajyoti Sinha, Stuart R. Lipsitz, Jianhang Lin:
Transform both sides model: A parametric approach. 903-913 - Giovanni Millo:
Maximum likelihood estimation of spatially and serially correlated panels with random effects. 914-933 - Nina Golyandina, Anton I. Korobeynikov:
Basic Singular Spectrum Analysis and forecasting with R. 934-954 - William H. Asquith:
Parameter estimation for the 4-parameter Asymmetric Exponential Power distribution by the method of L-moments using R. 955-970 - Francesco Bartolucci, Silvia Bacci, Michela Gnaldi:
MultiLCIRT: An R package for multidimensional latent class item response models. 971-985 - Manuel J. A. Eugster, Friedrich Leisch, Carolin Strobl:
(Psycho-)analysis of benchmark experiments: A formal framework for investigating the relationship between data sets and learning algorithms. 986-1000 - Liqun Wang, Chel Hee Lee:
Discretization-based direct random sample generation. 1001-1010 - Ching-Wei Cheng, Ying-Chao Hung, Narayanaswamy Balakrishnan:
Generating beta random numbers and Dirichlet random vectors in R: The package rBeta2009. 1011-1020 - Clément Chevalier, Victor Picheny, David Ginsbourger:
KrigInv: An efficient and user-friendly implementation of batch-sequential inversion strategies based on kriging. 1021-1034 - Victor Picheny, David Ginsbourger:
Noisy kriging-based optimization methods: A unified implementation within the DiceOptim package. 1035-1053 - Dirk Eddelbuettel, Conrad Sanderson:
RcppArmadillo: Accelerating R with high-performance C++ linear algebra. 1054-1063
- Steven Gilmour, Roger W. Payne:
Special issue on algorithms for design of experiments. 1064-1065
- Haftom T. Abebe, Frans E. S. Tan, Gerard J. P. Van Breukelen, Martijn P. F. Berger:
Bayesian D-optimal designs for the two parameter logistic mixed effects model. 1066-1076 - B. Almohaimeed, Alexander N. Donev:
Experimental designs for drug combination studies. 1077-1087 - Alexis Boukouvalas, Dan Cornford, Milan Stehlík:
Optimal design for correlated processes with input-dependent noise. 1088-1102 - Holger Dette, Andrey Pepelyshev, Anatoly A. Zhigljavsky:
'Nearly' universally optimal designs for models with correlated observations. 1103-1112 - Norbert Gaffke, Ulrike Graßhoff, Rainer Schwabe:
Algorithms for approximate linear regression design with application to a first order model with heteroscedasticity. 1113-1123 - Stelios D. Georgiou, Stella Stylianou, Manohar Aggarwal:
A class of composite designs for response surface methodology. 1124-1133 - Janet D. Godolphin, H. R. Warren:
An efficient procedure for the avoidance of disconnected incomplete block designs. 1134-1146 - Alex J. Gutman, Edward D. White, Dennis K. J. Lin, Raymond R. Hill:
Augmenting supersaturated designs with Bayesian D-optimality. 1147-1158 - Radoslav Harman, Lenka Filová:
Computing efficient exact designs of experiments using integer quadratic programming. 1159-1167 - S. Loeza-Serrano, Alexander N. Donev:
Construction of experimental designs for estimating variance components. 1168-1177 - Lu Lu, Christine M. Anderson-Cook, Dennis K. J. Lin:
Optimal designed experiments using a Pareto front search for focused preference of multiple objectives. 1178-1192 - Francesco Sambo, Matteo Borrotti, Kalliopi Mylona:
A coordinate-exchange two-phase local search algorithm for the D- and I-optimal designs of split-plot experiments. 1193-1207 - Chiara Tommasi, Juan M. Rodríguez-Díaz, M. Teresa Santos-Martín:
Integral approximations for computing optimum designs in random effects logistic regression models. 1208-1220
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