## Content

### 2014, Volume 74, Issue C

**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**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.