## Content

### 2014, Volume 71, Issue C

**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**1134-1146 An efficient procedure for the avoidance of disconnected incomplete block designs***by*Godolphin, J.D. & Warren, H.R.**1147-1158 Augmenting supersaturated designs with Bayesian D-optimality***by*Gutman, Alex J. & White, Edward D. & Lin, Dennis K.J. & Hill, Raymond R.**1159-1167 Computing efficient exact designs of experiments using integer quadratic programming***by*Harman, Radoslav & Filová, Lenka**1168-1177 Construction of experimental designs for estimating variance components***by*Loeza-Serrano, S. & Donev, A.N.**1178-1192 Optimal designed experiments using a Pareto front search for focused preference of multiple objectives***by*Lu, Lu & Anderson-Cook, Christine M. & Lin, Dennis K.J.**1193-1207 A coordinate-exchange two-phase local search algorithm for the D- and I-optimal designs of split-plot experiments***by*Sambo, Francesco & Borrotti, Matteo & Mylona, Kalliopi**1208-1220 Integral approximations for computing optimum designs in random effects logistic regression models***by*Tommasi, C. & Rodríguez-Díaz, J.M. & Santos-Martín, M.T.

### 2014, Volume 70, Issue C

**1-18 Automating the analysis of variance of orthogonal designs***by*Großmann, Heiko**19-34 An EM algorithm for the model fitting of Markovian binary trees***by*Hautphenne, Sophie & Fackrell, Mark**35-44 Simultaneous adjustment of bias and coverage probabilities for confidence intervals***by*Menéndez, P. & Fan, Y. & Garthwaite, P.H. & Sisson, S.A.**45-60 Towards Bayesian experimental design for nonlinear models that require a large number of sampling times***by*Ryan, Elizabeth G. & Drovandi, Christopher C. & Thompson, M. Helen & Pettitt, Anthony N.**61-66 Factor analysis parameter estimation from incomplete data***by*Roberts, W.J.J.**67-87 Discriminant analysis of multivariate time series: Application to diagnosis based on ECG signals***by*Maharaj, Elizabeth Ann & Alonso, Andrés M.**88-100 Fast regularized canonical correlation analysis***by*Cruz-Cano, Raul & Lee, Mei-Ling Ting**101-115 Semiparametric empirical likelihood confidence intervals for AUC under a density ratio model***by*Wang, Suohong & Zhang, Biao**116-126 Nonnegative-lasso and application in index tracking***by*Wu, Lan & Yang, Yuehan & Liu, Hanzhong**127-137 Test for homogeneity in gamma mixture models using likelihood ratio***by*Wong, Tony Siu Tung & Li, Wai Keung**138-152 Edge detection in sparse Gaussian graphical models***by*Luo, Shan & Chen, Zehua**153-171 Testing for heteroskedasticity and spatial correlation in a two way random effects model***by*Kouassi, Eugene & Mougoué, Mbodja & Sango, Joel & Bosson Brou, J.M. & Amba, Claude M.O. & Salisu, Afeez Adebare**172-182 Functional k-means inverse regression***by*Wang, Guochang & Lin, Nan & Zhang, Baoxue**183-197 Model detection for functional polynomial regression***by*Zhang, Tao & Zhang, Qingzhao & Wang, Qihua**198-211 Stabilizing the lasso against cross-validation variability***by*Roberts, S. & Nowak, G.**212-226 Dynamic seasonality in time series***by*So, Mike K.P. & Chung, Ray S.W.**227-240 The effect of the prior distribution in the Bayesian Adjustment for Confounding algorithm***by*Lefebvre, Geneviève & Atherton, Juli & Talbot, Denis**241-256 Variable selection and semiparametric efficient estimation for the heteroscedastic partially linear single-index model***by*Lai, Peng & Wang, Qihua & Zhou, Xiao-Hua**257-267 An ANOVA test for parameter estimability using data cloning with application to statistical inference for dynamic systems***by*Campbell, David & Lele, Subhash**268-280 Information criteria for Fay–Herriot model selection***by*Marhuenda, Yolanda & Morales, Domingo & del Carmen Pardo, María**281-294 A graph theoretic approach to simulation and classification***by*Kouritzin, Michael A. & Newton, Fraser & Wu, Biao**295-307 Cox proportional hazards models with frailty for negatively correlated employment processes***by*Xu, Wenjing & Pan, Qing & Gastwirth, Joseph L.**308-327 On wavelet-based testing for serial correlation of unknown form using Fan’s adaptive Neyman method***by*Li, Linyuan & Yao, Shan & Duchesne, Pierre**328-344 A cluster analysis of vote transitions***by*Puig, Xavier & Ginebra, Josep**345-361 Polarization of forecast densities: A new approach to time series classification***by*Liu, Shen & Maharaj, Elizabeth Ann & Inder, Brett**362-372 Estimator selection and combination in scalar-on-function regression***by*Goldsmith, Jeff & Scheipl, Fabian**373-386 A robust algorithm for template curve estimation based on manifold embedding***by*Dimeglio, Chloé & Gallón, Santiago & Loubes, Jean-Michel & Maza, Elie**387-394 On the optimally weighted z-test for combining probabilities from independent studies***by*Chen, Zhongxue & Nadarajah, Saralees**395-405 Asymmetric least squares support vector machine classifiers***by*Huang, Xiaolin & Shi, Lei & Suykens, Johan A.K.

### 2014, Volume 69, Issue C

**1-14 Finding the optimal cut-point for Gaussian and Gamma distributed biomarkers***by*Rota, Matteo & Antolini, Laura**15-39 Statistical study of asymmetry in cell lineage data***by*de Saporta, Benoîte & Gégout-Petit, Anne & Marsalle, Laurence**40-53 On the choice of test for a unit root when the errors are conditionally heteroskedastic***by*Westerlund, Joakim**54-66 Finding multivariate outliers with FastPCS***by*Vakili, Kaveh & Schmitt, Eric**67-80 The gamma-normal distribution: Properties and applications***by*Alzaatreh, Ayman & Famoye, Felix & Lee, Carl**81-91 Flexible modeling of survival data with covariates subject to detection limits via multiple imputation***by*Bernhardt, Paul W. & Wang, Huixia Judy & Zhang, Daowen**92-100 Goodness of fit test for discrete random variables***by*Lee, Sangyeol**101-113 Optimizing parameters in clinical trials with a randomized start or withdrawal design***by*Xiong, Chengjie & Luo, Jingqin & Gao, Feng & Morris, John C.**114-121 A GEE approach to determine sample size for pre- and post-intervention experiments with dropout***by*Zhang, Song & Cao, Jing & Ahn, Chul**122-132 Inclusion probabilities in partially rank ordered set sampling***by*Ozturk, Omer & Jafari Jozani, Mohammad**133-140 Simultaneous confidence intervals for ratios of means of several lognormal distributions: A parametric bootstrap approach***by*Sadooghi-Alvandi, S.M. & Malekzadeh, A.**141-153 Information criteria: How do they behave in different models?***by*Emiliano, Paulo C. & Vivanco, Mário J.F. & de Menezes, Fortunato S.**154-172 Recursive estimation of nonparametric regression with functional covariate***by*Amiri, Aboubacar & Crambes, Christophe & Thiam, Baba**173-183 Parameter estimation of two-level nonlinear mixed effects models using first order conditional linearization and the EM algorithm***by*Fu, Liyong & Wang, Mingliang & Lei, Yuancai & Tang, Shouzheng**184-197 Alternatives to the usual likelihood ratio test in mixed linear models***by*Stein, Markus Chagas & da Silva, Michel Ferreira & Duczmal, Luiz Henrique**198-207 Examining deterrence of adult sex crimes: A semi-parametric intervention time-series approach***by*Park, Jin-Hong & Bandyopadhyay, Dipankar & Letourneau, Elizabeth**208-219 Interquantile shrinkage and variable selection in quantile regression***by*Jiang, Liewen & Bondell, Howard D. & Wang, Huixia Judy**220-227 Bootstrap corrections of treatment effect estimates following selection***by*Rosenkranz, Gerd K.**228-242 Dimension reduction with missing response at random***by*Guo, Xu & Wang, Tao & Xu, Wangli & Zhu, Lixing**243-254 Approximate conditional least squares estimation of a nonlinear state-space model via an unscented Kalman filter***by*Ahn, Kwang Woo & Chan, Kung-Sik**255-268 Pairwise dynamic time warping for event data***by*Arribas-Gil, Ana & Müller, Hans-Georg

### 2013, Volume 67, Issue C

**1-14 Searching for a common pooling pattern among several samples***by*Álvarez-Esteban, P.C. & del Barrio, E. & Cuesta-Albertos, J.A. & Matrán, C.**15-24 Moment adjusted imputation for multivariate measurement error data with applications to logistic regression***by*Thomas, Laine & Stefanski, Leonard A. & Davidian, Marie**25-40 The spurious regression of AR(p) infinite-variance sequence in the presence of structural breaks***by*Jin, Hao & Zhang, Jinsuo & Zhang, Si & Yu, Cong**41-67 Lognormal lifetimes and likelihood-based inference for flexible cure rate models based on COM-Poisson family***by*Balakrishnan, N. & Pal, Suvra**68-83 Bayesian computing with INLA: New features***by*Martins, Thiago G. & Simpson, Daniel & Lindgren, Finn & Rue, Håvard**84-94 Robust methods for inferring sparse network structures***by*Vinciotti, Veronica & Hashem, Hussein**95-104 A method for detecting hidden additivity in two-factor unreplicated experiments***by*Franck, Christopher T. & Nielsen, Dahlia M. & Osborne, Jason A.**105-114 Entropy-based sliced inverse regression***by*Hino, Hideitsu & Wakayama, Keigo & Murata, Noboru**115-135 A variant of the parallel model for sample surveys with sensitive characteristics***by*Liu, Yin & Tian, Guo-Liang**136-148 Sparse high-dimensional fractional-norm support vector machine via DC programming***by*Guan, Wei & Gray, Alexander**149-161 Robust fitting of a Weibull model with optional censoring***by*Yang, Jingjing & Scott, David W.**162-174 Nonparametric feature screening***by*Lin, Lu & Sun, Jing & Zhu, Lixing**175-184 Combining functions and the closure principle for performing follow-up tests in functional analysis of variance***by*Vsevolozhskaya, O.A. & Greenwood, M.C. & Bellante, G.J. & Powell, S.L. & Lawrence, R.L. & Repasky, K.S.**185-198 Bayesian bandwidth estimation for a nonparametric functional regression model with unknown error density***by*Shang, Han Lin**199-212 Partially linear single index Cox regression model in nested case-control studies***by*Shang, Shulian & Liu, Mengling & Zeleniuch-Jacquotte, Anne & Clendenen, Tess V. & Krogh, Vittorio & Hallmans, Goran & Lu, Wenbin**213-225 Some properties of multivariate INAR(1) processes***by*Pedeli, Xanthi & Karlis, Dimitris**226-235 Comparison of MCMC algorithms for the estimation of Tobit model with non-normal error: The case of asymmetric Laplace distribution***by*Wichitaksorn, Nuttanan & Tsurumi, Hiroki**236-247 Introduction to face recognition and evaluation of algorithm performance***by*Givens, G.H. & Beveridge, J.R. & Phillips, P.J. & Draper, B. & Lui, Y.M. & Bolme, D.**248-257 A semi-parametric approach to analysis of event duration and prevalence***by*Wang, Jixian & Quartey, George**258-267 Contaminated Variance–Mean mixing model***by*Fung, Thomas & Wang, Joanna J.J. & Seneta, Eugene**268-281 Estimation using hybrid censored data from a two-parameter distribution with bathtub shape***by*Rastogi, Manoj Kumar & Tripathi, Yogesh Mani**282-298 Least-squares estimation of a convex discrete distribution***by*Durot, Cécile & Huet, Sylvie & Koladjo, François & Robin, Stéphane

### 2013, Volume 66, Issue C

**1-7 Two algorithms for fitting constrained marginal models***by*Evans, R.J. & Forcina, A.**8-18 OLS with multiple high dimensional category variables***by*Gaure, Simen**19-31 Inference for variograms***by*Bowman, Adrian W. & Crujeiras, Rosa M.**32-54 Logistic regression with outcome and covariates missing separately or simultaneously***by*Hsieh, Shu-Hui & Li, Chin-Shang & Lee, Shen-Ming**55-69 Cross Validation and Maximum Likelihood estimations of hyper-parameters of Gaussian processes with model misspecification***by*Bachoc, François**70-81 Nonparametric meta-analysis of independent samples of records***by*Amini, Morteza & Balakrishnan, N.**82-88 Multidimensional medians and uniqueness***by*Zuo, Yijun**89-100 M-type smoothing spline estimators for principal functions***by*Lee, Seokho & Shin, Hyejin & Billor, Nedret**101-116 Empirical likelihood inference for mean functionals with nonignorably missing response data***by*Zhao, Hui & Zhao, Pu-Ying & Tang, Nian-Sheng**117-128 Optimisation of interacting particle systems for rare event estimation***by*Morio, Jérôme & Jacquemart, Damien & Balesdent, Mathieu & Marzat, Julien**129-139 Estimating a unitary effect summary based on combined survival and quantitative outcomes***by*Lin, Huazhen & Li, Yi & Tan, Ming T.**140-149 Optimal feature selection for sparse linear discriminant analysis and its applications in gene expression data***by*Wang, Cheng & Cao, Longbing & Miao, Baiqi**150-160 Statistical inference for partially linear stochastic models with heteroscedastic errors***by*Wang, Xiaoguang & Lu, Dawei & Song, Lixin**161-177 Conjugate and conditional conjugate Bayesian analysis of discrete graphical models of marginal independence***by*Ntzoufras, Ioannis & Tarantola, Claudia**178-192 Cluster Forests***by*Yan, Donghui & Chen, Aiyou & Jordan, Michael I.**193-201 Two-way incremental seriation in the temporal domain with three-dimensional visualization: Making sense of evolving high-dimensional datasets***by*Wittek, Peter**202-216 New prediction method for the mixed logistic model applied in a marketing problem***by*Tamura, Karin Ayumi & Giampaoli, Viviana

### 2013, Volume 65, Issue C

**4-12 Density estimation for data with rounding errors***by*Wang, B. & Wertelecki, W.**13-28 Detecting influential data points for the Hill estimator in Pareto-type distributions***by*Hubert, Mia & Dierckx, Goedele & Vanpaemel, Dina**29-45 Robust distances for outlier-free goodness-of-fit testing***by*Cerioli, Andrea & Farcomeni, Alessio & Riani, Marco**46-55 Robust functional linear regression based on splines***by*Maronna, Ricardo A. & Yohai, Victor J.**56-67 Variable selection in high-dimensional partially linear additive models for composite quantile regression***by*Guo, Jie & Tang, Manlai & Tian, Maozai & Zhu, Kai**68-79 Robust estimation for vector autoregressive models***by*Muler, Nora & Yohai, V´ictor J.**80-97 Robust tests in generalized linear models with missing responses***by*Bianco, Ana M. & Boente, Graciela & Rodrigues, Isabel M.**98-112 Robust minimum information loss estimation***by*Lind, John C. & Wiens, Douglas P. & Yohai, Victor J.

### 2013, Volume 64, Issue C

**1-19 Mixture of D-vine copulas for modeling dependence***by*Kim, Daeyoung & Kim, Jong-Min & Liao, Shu-Min & Jung, Yoon-Sung**20-33 Power Lindley distribution and associated inference***by*Ghitany, M.E. & Al-Mutairi, D.K. & Balakrishnan, N. & Al-Enezi, L.J.**34-50 A new extended Birnbaum–Saunders regression model for lifetime modeling***by*Lemonte, Artur J.**51-70 Assessing classifiers in terms of the partial area under the ROC curve***by*Yousef, Waleed A.**71-86 Minimum disparity estimation: Improved efficiency through inlier modification***by*Mandal, Abhijit & Basu, Ayanendranath**87-98 Simultaneous confidence intervals for comparing margins of multivariate binary data***by*Klingenberg, Bernhard & Satopää, Ville**99-112 Monitoring the covariance matrix with fewer observations than variables***by*Maboudou-Tchao, Edgard M. & Agboto, Vincent**113-131 Bispectral-based methods for clustering time series***by*Harvill, Jane L. & Ravishanker, Nalini & Ray, Bonnie K.**132-152 Stable graphical model estimation with Random Forests for discrete, continuous, and mixed variables***by*Fellinghauer, Bernd & Bühlmann, Peter & Ryffel, Martin & von Rhein, Michael & Reinhardt, Jan D.**153-164 Linear regression models with slash-elliptical errors***by*Alcantara, Izabel Cristina & Cysneiros, Francisco José A.**165-179 Generalised interval estimation in the random effects meta regression model***by*Friedrich, Thomas & Knapp, Guido**180-191 Two step composite quantile regression for single-index models***by*Jiang, Rong & Zhou, Zhan-Gong & Qian, Wei-Min & Chen, Yong**192-208 A Bayesian multivariate probit for ordinal data with semiparametric random-effects***by*Kim, Jung Seek & Ratchford, Brian T.**209-219 Conjugate priors and variable selection for Bayesian quantile regression***by*Alhamzawi, Rahim & Yu, Keming**220-236 A predictive deviance criterion for selecting a generative model in semi-supervised classification***by*Vandewalle, Vincent & Biernacki, Christophe & Celeux, Gilles & Govaert, Gérard**237-252 Bayesian inference in nonlinear mixed-effects models using normal independent distributions***by*Lachos, Victor H. & Castro, Luis M. & Dey, Dipak K.**253-268 An empirical study of tests for uniformity in multidimensional data***by*Petrie, Adam & Willemain, Thomas R.**269-280 Statistical inference on survival data in group-parallel clinical trials with treatment switching***by*Ding, Chang & Tse, Siu-keung & Yang, Ronghai**281-298 Logistic regression with weight grouping priors***by*Korzeń, M. & Jaroszewicz, S. & Klęsk, P.**299-313 Objective Bayesian analysis for bivariate Marshall–Olkin exponential distribution***by*Guan, Qiang & Tang, Yincai & Xu, Ancha

### 2013, Volume 63, Issue C

**1-15 Generalized Birnbaum–Saunders kernel density estimators and an analysis of financial data***by*Marchant, Carolina & Bertin, Karine & Leiva, Víctor & Saulo, Helton**16-30 Performance of parametric survival models under non-random interval censoring: A simulation study***by*Pantazis, Nikos & Kenward, Michael G. & Touloumi, Giota**31-41 Multiple choice from competing regression models under multicollinearity based on standardized update***by*Ueki, Masao & Kawasaki, Yoshinori