# Elsevier

# Computational Statistics & Data Analysis

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### 2014, Volume 77, Issue C

**336-351 Monotone splines lasso***by*Bergersen, Linn Cecilie & Tharmaratnam, Kukatharmini & Glad, Ingrid K.**352-370 Adaptive likelihood ratio approaches for the detection of space–time disease clusters***by*de Lima, Max Sousa & Duczmal, Luiz Henrique**371-382 Asymmetric ν-tube support vector regression***by*Huang, Xiaolin & Shi, Lei & Pelckmans, Kristiaan & Suykens, Johan A.K.

### 2014, Volume 76, Issue C

**4-19 The univariate MT-STAR model and a new linearity and unit root test procedure***by*Addo, Peter Martey & Billio, Monica & Guégan, Dominique**20-33 Sovereign credit ratings, market volatility, and financial gains***by*Afonso, António & Gomes, Pedro & Taamouti, Abderrahim**34-42 Maximum likelihood estimates for positive valued dynamic score models; The DySco package***by*Andres, Philipp**43-60 Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks***by*Audrino, Francesco**61-75 Maximum likelihood estimation of the Markov-switching GARCH model***by*Augustyniak, Maciej**76-94 Modeling tails of aggregate economic processes in a stochastic growth model***by*Auray, Stéphane & Eyquem, Aurélien & Jouneau-Sion, Frédéric**95-115 Parameter cascading for panel models with unknown number of unobserved factors: An application to the credit spread puzzle***by*Bada, Oualid & Kneip, Alois**116-131 Modified information criteria and selection of long memory time series models***by*Baillie, Richard T. & Kapetanios, George & Papailias, Fotis**132-143 On the usefulness of cross-validation for directional forecast evaluation***by*Bergmeir, Christoph & Costantini, Mauro & Benítez, José M.**144-157 Long memory with stochastic variance model: A recursive analysis for US inflation***by*Bos, Charles S. & Koopman, Siem Jan & Ooms, Marius**158-171 Estimating GARCH-type models with symmetric stable innovations: Indirect inference versus maximum likelihood***by*Calzolari, Giorgio & Halbleib, Roxana & Parrini, Alessandro**172-185 Robust ranking of multivariate GARCH models by problem dimension***by*Caporin, Massimiliano & McAleer, Michael**186-193 Modelling breaks and clusters in the steady states of macroeconomic variables***by*Chan, Joshua C.C. & Koop, Gary**194-209 Bayesian estimation of smoothly mixing time-varying parameter GARCH models***by*Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H.**210-236 Multivariate GARCH estimation via a Bregman-proximal trust-region method***by*Chrétien, Stéphane & Ortega, Juan-Pablo**237-247 Numerical distribution functions for seasonal unit root tests***by*Diaz-Emparanza, Ignacio**248-261 Testing for serial independence of panel errors***by*Du, Zaichao**262-282 Multiple break detection in the correlation structure of random variables***by*Galeano, Pedro & Wied, Dominik**283-290 Interest rate spreads and output: A time scale decomposition analysis using wavelets***by*Gallegati, Marco & Ramsey, James B. & Semmler, Willi**291-300 Comparison of specification tests for GARCH models***by*Ghoudi, Kilani & Rémillard, Bruno**301-319 When long memory meets the Kalman filter: A comparative study***by*Grassi, Stefano & Santucci de Magistris, Paolo**320-338 EGARCH models with fat tails, skewness and leverage***by*Harvey, Andrew & Sucarrat, Genaro**339-358 Infinite-order, long-memory heterogeneous autoregressive models***by*Hwang, Eunju & Shin, Dong Wan**359-376 Estimation of risk measures in energy portfolios using modern copula techniques***by*Jäschke, Stefan**377-390 Panel cointegration testing in the presence of a time trend***by*Karaman Örsal, Deniz Dilan & Droge, Bernd**391-407 Testing for unit roots in short panels allowing for a structural break***by*Karavias, Yiannis & Tzavalis, Elias**408-423 Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models***by*Kastner, Gregor & Frühwirth-Schnatter, Sylvia**424-448 Improved variance estimation of maximum likelihood estimators in stable first-order dynamic regression models***by*Kiviet, Jan F. & Phillips, Garry D.A.**449-463 Efficient importance sampling in mixture frameworks***by*Kleppe, Tore Selland & Liesenfeld, Roman**464-488 The indirect continuous-GMM estimation***by*Kotchoni, Rachidi**489-501 A likelihood ratio type test for invertibility in moving average processes***by*Larsson, Rolf**502-522 Testing for persistence change in fractionally integrated models: An application to world inflation rates***by*Martins, Luis F. & Rodrigues, Paulo M.M.**523-535 SCOMDY models based on pair-copula constructions with application to exchange rates***by*Min, Aleksey & Czado, Claudia**536-555 Forecasting with a noncausal VAR model***by*Nyberg, Henri & Saikkonen, Pentti**556-576 Variance clustering improved dynamic conditional correlation MGARCH estimators***by*Aielli, Gian Piero & Caporin, Massimiliano**577-587 A joint test for structural stability and a unit root in autoregressions***by*Pitarakis, Jean-Yves**588-605 Bayesian option pricing using mixed normal heteroskedasticity models***by*Rombouts, Jeroen V.K. & Stentoft, Lars**606-617 Dynamic factor multivariate GARCH model***by*Santos, André A.P. & Moura, Guilherme V.**618-641 Realized stochastic volatility with leverage and long memory***by*Shirota, Shinichiro & Hizu, Takayuki & Omori, Yasuhiro**642-654 A flexible and automated likelihood based framework for inference in stochastic volatility models***by*Skaug, Hans J. & Yu, Jun**655-671 Vine-copula GARCH model with dynamic conditional dependence***by*So, Mike K.P. & Yeung, Cherry Y.T.**672-686 Regime switches in the dependence structure of multidimensional financial data***by*Stöber, Jakob & Czado, Claudia**687-707 Extended stochastic volatility models incorporating realised measures***by*Venter, J.H. & de Jongh, P.J.**708-722 Optimal design of Fourier estimator in the presence of microstructure noise***by*Wang, Fangfang**723-736 A fluctuation test for constant Spearman’s rho with nuisance-free limit distribution***by*Wied, Dominik & Dehling, Herold & van Kampen, Maarten & Vogel, Daniel**737-759 Solving norm constrained portfolio optimization via coordinate-wise descent algorithms***by*Yen, Yu-Min & Yen, Tso-Jung

### 2014, Volume 75, Issue C

**1-14 Kalman filter variants in the closed skew normal setting***by*Rezaie, Javad & Eidsvik, Jo**15-27 A joint convex penalty for inverse covariance matrix estimation***by*Maurya, Ashwini**28-38 Bayesian estimation of adaptive bandwidth matrices in multivariate kernel density estimation***by*Zougab, Nabil & Adjabi, Smail & Kokonendji, Célestin C.**39-52 Group subset selection for linear regression***by*Guo, Yi & Berman, Mark & Gao, Junbin**53-65 Bayesian variable selection under the proportional hazards mixed-effects model***by*Lee, Kyeong Eun & Kim, Yongku & Xu, Ronghui**66-80 Robust estimation of the parameters of g-and-h distributions, with applications to outlier detection***by*Xu, Yihuan & Iglewicz, Boris & Chervoneva, Inna**81-95 Classification of molecular sequence data using Bayesian phylogenetic mixture models***by*Loza-Reyes, E. & Hurn, M.A. & Robinson, A.**96-111 Lower confidence limit for reliability based on grouped data using a quantile-filling algorithm***by*Zhang, Mimi & Hu, Qingpei & Xie, Min & Yu, Dan**112-123 Nonnegative bias reduction methods for density estimation using asymmetric kernels***by*Hirukawa, Masayuki & Sakudo, Mari**124-141 A random-projection based test of Gaussianity for stationary processes***by*Nieto-Reyes, Alicia & Cuesta-Albertos, Juan Antonio & Gamboa, Fabrice**142-150 A frame based shrinkage procedure for fast oscillating functions***by*De Canditiis, Daniela**151-161 Consistency-adjusted alpha allocation methods for a time-to-event analysis of composite endpoints***by*Rauch, G. & Wirths, M. & Kieser, M.**162-178 Family of power divergence spatial scan statistics***by*Zhang, Tonglin & Lin, Ge**179-189 A frequency domain test for detecting nonstationary time series***by*Chen, Yen-Hung & Hsu, Nan-Jung**190-202 Choice of generalized linear mixed models using predictive crossvalidation***by*Braun, Julia & Sabanés Bové, Daniel & Held, Leonhard**203-216 Finding the limit of diverging components in three-way Candecomp/Parafac—A demonstration of its practical merits***by*Stegeman, Alwin**217-226 The influence of a covariate on optimal designs in longitudinal studies with discrete-time survival endpoints***by*Safarkhani, Maryam & Moerbeek, Mirjam**227-238 Probabilistic wind speed forecasting using Bayesian model averaging with truncated normal components***by*Baran, Sándor**239-247 A hybrid approach for regression analysis with block missing data***by*Li, Zhengbang & Li, Qizhai & Han, Chien-Pai & Li, Bo**248-264 Computing confidence intervals for log-concave densities***by*Azadbakhsh, Mahdis & Jankowski, Hanna & Gao, Xin

### 2014, Volume 74, Issue C

**1-16 Wald-type rank tests: A GEE approach***by*Fan, Chunpeng & Zhang, Donghui**17-25 Improving mixture tree construction using better EM algorithms***by*Chen, Shu-Chuan (Grace) & Lindsay, Bruce**26-38 A high-dimensional two-sample test for the mean using random subspaces***by*Thulin, Måns**39-51 Sample size determination for paired right-censored data based on the difference of Kaplan–Meier estimates***by*Su, Pei-Fang & Li, Chung-I & Shyr, Yu**52-63 Analysis of multivariate survival data with Clayton regression models under conditional and marginal formulations***by*He, W.**64-80 A dynamic linear model with extended skew-normal for the initial distribution of the state parameter***by*Cabral, Celso Rômulo Barbosa & da-Silva, Cibele Queiroz & Migon, Helio S.**81-94 Fast balanced sampling for highly stratified population***by*Hasler, Caren & Tillé, Yves**95-109 TVICA—Time varying independent component analysis and its application to financial data***by*Chen, Ray-Bing & Chen, Ying & Härdle, Wolfgang K.**110-124 Improved likelihood inference in generalized linear models***by*Vargas, Tiago M. & Ferrari, Silvia L.P. & Lemonte, Artur J.**125-141 Spatial prediction in the presence of left-censoring***by*Schelin, Lina & Sjöstedt-de Luna, Sara**142-156 On the maximum penalized likelihood approach for proportional hazard models with right censored survival data***by*Ma, Jun & Heritier, Stephane & Lô, Serigne N.**157-179 Dimension reduction in principal component analysis for trees***by*Alfaro, Carlos A. & Aydın, Burcu & Valencia, Carlos E. & Bullitt, Elizabeth & Ladha, Alim**181-197 Learning algorithms may perform worse with increasing training set size: Algorithm–data incompatibility***by*Yousef, Waleed A. & Kundu, Subrata**198-208 Bayesian semiparametric model for spatially correlated interval-censored survival data***by*Pan, Chun & Cai, Bo & Wang, Lianming & Lin, Xiaoyan**209-216 Least squares estimation of a k-monotone density function***by*Chee, Chew-Seng & Wang, Yong**217-227 Sample size calculation for the proportional hazards model with a time-dependent covariate***by*Wang, Songfeng & Zhang, Jiajia & Lu, Wenbin

### 2014, Volume 73, Issue C

**1-15 Exploratory time varying lagged regression: Modeling association of cognitive and functional trajectories with expected clinic visits in older adults***by*Şentürk, Damla & Ghosh, Samiran & Nguyen, Danh V.**16-26 Eliminating bias due to censoring in Kendall’s tau estimators for quasi-independence of truncation and failure***by*Austin, Matthew D. & Betensky, Rebecca A.**27-39 A non-parametric method to estimate the number of clusters***by*Fujita, André & Takahashi, Daniel Y. & Patriota, Alexandre G.**40-52 Efficient optimization of the likelihood function in Gaussian process modelling***by*Butler, A. & Haynes, R.D. & Humphries, T.D. & Ranjan, P.**53-68 Theoretical and practical aspects of the quadratic error in the local linear estimation of the conditional density for functional data***by*Rachdi, Mustapha & Laksaci, Ali & Demongeot, Jacques & Abdali, Abdel & Madani, Fethi**69-86 Asymptotic distributions for quasi-efficient estimators in echelon VARMA models***by*Dufour, Jean-Marie & Jouini, Tarek**87-102 Efficient estimation of the link function parameter in a robust Bayesian binary regression model***by*Roy, Vivekananda**103-111 Nonparametric tests for panel count data with unequal observation processes***by*Li, Yang & Zhao, Hui & Sun, Jianguo & Kim, KyungMann**112-128 Confidence intervals for quantiles in finite populations with randomized nomination sampling***by*Nourmohammadi, Mohammad & Jafari Jozani, Mohammad & Johnson, Brad C.**129-145 Asymptotic distribution of the EPMS estimator for financial derivatives pricing***by*Huang, Shih-Feng & Tu, Ya-Ting**146-162 Computation of maximum likelihood estimates for multiresponse generalized linear mixed models with non-nested, correlated random effects***by*Karl, Andrew T. & Yang, Yan & Lohr, Sharon L.**163-176 Mean field variational Bayesian inference for support vector machine classification***by*Luts, Jan & Ormerod, John T.**177-188 A Bayesian semiparametric regression model for reliability data using effective age***by*Li, Li & Hanson, Timothy E.**189-204 Modelling trends in road accident frequency— Bayesian inference for rates with uncertain exposure***by*Lloyd, Louise K. & Forster, Jonathan J.

### 2014, Volume 72, Issue C

**1-12 Functionally induced priors for componentwise Gibbs sampler in the analysis of supersaturated designs***by*Huang, Hengzhen & Yang, Jinyu & Liu, Min-Qian**13-29 Unimodal density estimation using Bernstein polynomials***by*Turnbull, Bradley C. & Ghosh, Sujit K.**30-44 Reinforcement learning-based design of sampling policies under cost constraints in Markov random fields: Application to weed map reconstruction***by*Bonneau, Mathieu & Gaba, Sabrina & Peyrard, Nathalie & Sabbadin, Régis**45-56 Testing constancy in monotone response models***by*Colubi, Ana & Domínguez-Menchero, J. Santos & González-Rodríguez, Gil**57-76 Nonparametric kernel density estimation near the boundary***by*Malec, Peter & Schienle, Melanie**77-91 Inference for longitudinal data with nonignorable nonmonotone missing responses***by*Sinha, Sanjoy K. & Kaushal, Amit & Xiao, Wenzhong**92-104 Recursive partitioning for missing data imputation in the presence of interaction effects***by*Doove, L.L. & Van Buuren, S. & Dusseldorp, E.**105-127 Time-efficient estimation of conditional mutual information for variable selection in classification***by*Todorov, Diman & Setchi, Rossi**128-146 Marginal reversible jump Markov chain Monte Carlo with application to motor unit number estimation***by*Drovandi, Christopher C. & Pettitt, Anthony N. & Henderson, Robert D. & McCombe, Pamela A.**147-157 Bayesian test on equality of score parameters in the order restricted RC association model***by*Oh, Man-Suk**158-175 Nonparametric variable selection and classification: The CATCH algorithm***by*Tang, Shijie & Chen, Lisha & Tsui, Kam-Wah & Doksum, Kjell**176-189 An ExPosition of multivariate analysis with the singular value decomposition in R***by*Beaton, Derek & Chin Fatt, Cherise R. & Abdi, Hervé**190-204 Nonparametric estimation of the tree structure of a nested Archimedean copula***by*Segers, Johan & Uyttendaele, Nathan**205-218 Automated learning of factor analysis with complete and incomplete data***by*Zhao, Jianhua & Shi, Lei**219-226 Plasmode simulation for the evaluation of pharmacoepidemiologic methods in complex healthcare databases***by*Franklin, Jessica M. & Schneeweiss, Sebastian & Polinski, Jennifer M. & Rassen, Jeremy A.**227-240 Approximate inference for spatial functional data on massively parallel processors***by*Rakêt, Lars Lau & Markussen, Bo**241-251 Power and sample size calculations for Poisson and zero-inflated Poisson regression models***by*Channouf, Nabil & Fredette, Marc & MacGibbon, Brenda**252-272 Sequential Monte Carlo EM for multivariate probit models***by*Moffa, Giusi & Kuipers, Jack**273-281 The jackknife’s edge: Inference for censored regression quantiles***by*Portnoy, Stephen**282-297 Discrete particle swarm optimization for constructing uniform design on irregular regions***by*Chen, Ray-Bing & Hsu, Yen-Wen & Hung, Ying & Wang, Weichung**298-314 A generalized multiple-try version of the Reversible Jump algorithm***by*Pandolfi, Silvia & Bartolucci, Francesco & Friel, Nial**315-327 Covariance structure regularization via entropy loss function***by*Lin, Lijing & Higham, Nicholas J. & Pan, Jianxin

### 2014, Volume 71, Issue C

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