# Elsevier

# Computational Statistics & Data Analysis

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### 2016, Volume 97, Issue C

**1-15 Mixture of functional linear models and its application to CO2-GDP functional data***by*Wang, Shaoli & Huang, Mian & Wu, Xing & Yao, Weixin**16-32 Fast computation of reconciled forecasts for hierarchical and grouped time series***by*Hyndman, Rob J. & Lee, Alan J. & Wang, Earo**33-46 A unifying approach to the shape and change-point hypotheses in the discrete univariate exponential family***by*Hirotsu, Chihiro & Yamamoto, Shoichi & Tsuruta, Harukazu**47-59 Semiparametric regression analysis of panel count data allowing for within-subject correlation***by*Yao, Bin & Wang, Lianming & He, Xin**60-70 Natural coordinate descent algorithm for L1-penalised regression in generalised linear models***by*Michoel, Tom**71-86 An exact approach to Bayesian sequential change point detection***by*Ruggieri, Eric & Antonellis, Marcus**87-97 A high-dimension two-sample test for the mean using cluster subspaces***by*Zhang, Jie & Pan, Meng**98-113 Sequentially Constrained Monte Carlo***by*Golchi, Shirin & Campbell, David A.**114-132 Multivariate models for dependent clusters of variables with conditional independence given aggregation variables***by*Joe, Harry & Sang, Peijun**133-150 Clustering, classification, discriminant analysis, and dimension reduction via generalized hyperbolic mixtures***by*Morris, Katherine & McNicholas, Paul D.**151-168 Robust testing for superiority between two regression curves***by*Boente, Graciela & Pardo-Fernández, Juan Carlos**169-183 A bivariate Birnbaum–Saunders regression model***by*Vilca, Filidor & Romeiro, Renata G. & Balakrishnan, N.

### 2016, Volume 96, Issue C

**1-11 The Expectation–Maximization approach for Bayesian quantile regression***by*Zhao, Kaifeng & Lian, Heng**12-23 HHCART: An oblique decision tree***by*Wickramarachchi, D.C. & Robertson, B.L. & Reale, M. & Price, C.J. & Brown, J.**24-39 Simultaneous mean and covariance estimation of partially linear models for longitudinal data with missing responses and covariate measurement error***by*Qin, Guoyou & Zhang, Jiajia & Zhu, Zhongyi**40-56 Estimation and variable selection for proportional response data with partially linear single-index models***by*Zhao, Weihua & Lian, Heng & Zhang, Riquan & Lai, Peng**57-73 Random forest for ordinal responses: Prediction and variable selection***by*Janitza, Silke & Tutz, Gerhard & Boulesteix, Anne-Laure**74-86 Estimation of survival and capture probabilities in open population capture–recapture models when covariates are subject to measurement error***by*Stoklosa, Jakub & Dann, Peter & Huggins, Richard M. & Hwang, Wen-Han**87-103 Structured variable selection via prior-induced hierarchical penalty functions***by*Yen, Tso-Jung & Yen, Yu-Min**104-119 Regularized estimation for the least absolute relative error models with a diverging number of covariates***by*Xia, Xiaochao & Liu, Zhi & Yang, Hu**120-132 Frequentist nonparametric goodness-of-fit tests via marginal likelihood ratios***by*Hart, Jeffrey D. & Choi, Taeryon & Yi, Seongbaek**133-144 Bayesian analysis of two-piece location–scale models under reference priors with partial information***by*Tu, Shiyi & Wang, Min & Sun, Xiaoqian**145-158 Graph-theoretic multisample tests of equality in distribution for high dimensional data***by*Petrie, Adam

### 2016, Volume 95, Issue C

**1-16 Bayesian variable selection for finite mixture model of linear regressions***by*Lee, Kuo-Jung & Chen, Ray-Bing & Wu, Ying Nian**17-23 Local computations of the iterative proportional scaling procedure for hierarchical models***by*Xu, Ping-Feng & Sun, Jubo & Shan, Na**24-38 Multiply imputing missing values in data sets with mixed measurement scales using a sequence of generalised linear models***by*Lee, Min Cherng & Mitra, Robin**39-56 A Bayesian hierarchical model for spatial extremes with multiple durations***by*Wang, Yixin & So, Mike K.P.**57-74 A nonlinear population Monte Carlo scheme for the Bayesian estimation of parameters of α-stable distributions***by*Koblents, Eugenia & Míguez, Joaquín & Rodríguez, Marco A. & Schmidt, Alexandra M.**75-82 Testing the order of a population spectral distribution for high-dimensional data***by*Qin, Yingli & Li, Weiming**83-94 On Moran’s I coefficient under heterogeneity***by*Zhang, Tonglin & Lin, Ge**95-108 Comparison of linear shrinkage estimators of a large covariance matrix in normal and non-normal distributions***by*Ikeda, Yuki & Kubokawa, Tatsuya & Srivastava, Muni S.**109-121 On quadratic logistic regression models when predictor variables are subject to measurement error***by*Stoklosa, Jakub & Huang, Yih-Huei & Furlan, Elise & Hwang, Wen-Han**122-132 Confidence intervals for the ratio of two Poisson rates under one-way differential misclassification using double sampling***by*Kahle, David J. & Young, Phil D. & Greer, Brandi A. & Young, Dean M.**133-149 Hierarchical independent component analysis: A multi-resolution non-orthogonal data-driven basis***by*Secchi, Piercesare & Vantini, Simone & Zanini, Paolo**150-160 Comparing conditional survival functions with missing population marks in a competing risks model***by*Bandyopadhyay, Dipankar & Jácome, M. Amalia**161-175 A time dependent Bayesian nonparametric model for air quality analysis***by*Gutiérrez, Luis & Mena, Ramsés H. & Ruggiero, Matteo**176-191 Case deletion diagnostics for GMM estimation***by*Shi, Lei & Lu, Jun & Zhao, Jianhua & Chen, Gemai**192-206 Exploratory failure time analysis in large scale genomics***by*Cheng, Cheng**207-221 A SAEM algorithm for fused lasso penalized NonLinear Mixed Effect Models: Application to group comparison in pharmacokinetics***by*Ollier, Edouard & Samson, Adeline & Delavenne, Xavier & Viallon, Vivian**222-239 Regularized quantile regression under heterogeneous sparsity with application to quantitative genetic traits***by*He, Qianchuan & Kong, Linglong & Wang, Yanhua & Wang, Sijian & Chan, Timothy A. & Holland, Eric**243-258 Fast computation of large scale marginal extremes with multi-dimensional covariates***by*Raghupathi, Laks & Randell, David & Ewans, Kevin & Jonathan, Philip

### 2016, Volume 94, Issue C

**1-19 Nonlinear expectile regression with application to Value-at-Risk and expected shortfall estimation***by*Kim, Minjo & Lee, Sangyeol**20-32 A triplot for multiclass classification visualisation***by*Gardner-Lubbe, Sugnet**33-48 Principal minimax support vector machine for sufficient dimension reduction with contaminated data***by*Zhou, Jingke & Zhu, Lixing**49-62 Fast and accurate computation for kernel estimators***by*Tang, Qingguo & Karunamuni, Rohana J.**63-74 A likelihood-free filtering method via approximate Bayesian computation in evaluating biological simulation models***by*Hasegawa, Takanori & Niida, Atsushi & Mori, Tomoya & Shimamura, Teppei & Yamaguchi, Rui & Miyano, Satoru & Akutsu, Tatsuya & Imoto, Seiya**75-85 A semiparametric scale-mixture regression model and predictive recursion maximum likelihood***by*Martin, Ryan & Han, Zhen**86-97 Diagnostic checking of the vector multiplicative error model***by*Ng, F.C. & Li, W.K. & Yu, Philip L.H.**98-119 A propensity score adjustment method for regression models with nonignorable missing covariates***by*Jiang, Depeng & Zhao, Puying & Tang, Niansheng**120-135 The Hawkes process with renewal immigration & its estimation with an EM algorithm***by*Wheatley, Spencer & Filimonov, Vladimir & Sornette, Didier**136-160 The generalized modified Weibull power series distribution: Theory and applications***by*Bagheri, S.F. & Bahrami Samani, E. & Ganjali, M.**161-174 Nonparametric estimation of a quantile density function by wavelet methods***by*Chesneau, Christophe & Dewan, Isha & Doosti, Hassan**175-192 A general procedure to combine estimators***by*Lavancier, F. & Rochet, P.**193-209 Gaussian quadrature approximations in mixed hidden Markov models for longitudinal data: A simulation study***by*Marino, Maria Francesca & Alfó, Marco**210-220 Parametric cost-effectiveness inference with skewed data***by*Bebu, Ionut & Luta, George & Mathew, Thomas & Kennedy, Paul A. & Agan, Brian K.**221-237 On stepwise pattern recovery of the fused Lasso***by*Qian, Junyang & Jia, Jinzhu**238-249 A sequential logistic regression classifier based on mixed effects with applications to longitudinal data***by*Zhang, Xin & Jeske, Daniel R. & Li, Jun & Wong, Vance**250-264 Multiobjective optimization of expensive-to-evaluate deterministic computer simulator models***by*Svenson, Joshua & Santner, Thomas**265-274 Fixed factor analysis with clustered factor score constraint***by*Uno, Kohei & Satomura, Hironori & Adachi, Kohei**275-286 A modified local quadratic approximation algorithm for penalized optimization problems***by*Lee, Sangin & Kwon, Sunghoon & Kim, Yongdai**287-301 Adaptive conditional feature screening***by*Lin, Lu & Sun, Jing**302-316 Jackknife empirical likelihood test for high-dimensional regression coefficients***by*Zang, Yangguang & Zhang, Sanguo & Li, Qizhai & Zhang, Qingzhao**317-329 Interaction models for functional regression***by*Usset, Joseph & Staicu, Ana-Maria & Maity, Arnab**330-350 Simplicial principal component analysis for density functions in Bayes spaces***by*Hron, K. & Menafoglio, A. & Templ, M. & Hrůzová, K. & Filzmoser, P.**351-362 Classification of multiple time signals using localized frequency characteristics applied to industrial process monitoring***by*Aykroyd, Robert G. & Barber, Stuart & Miller, Luke R.**363-371 Analysis of long series of longitudinal ordinal data using marginalized models***by*Lee, Keunbaik & Sohn, Insuk & Kim, Donguk**372-390 Multivariate Fay–Herriot models for small area estimation***by*Benavent, Roberto & Morales, Domingo

### 2016, Volume 93, Issue C

**5-17 Identifying connected components in Gaussian finite mixture models for clustering***by*Scrucca, Luca**18-30 Clustering with the multivariate normal inverse Gaussian distribution***by*O’Hagan, Adrian & Murphy, Thomas Brendan & Gormley, Isobel Claire & McNicholas, Paul D. & Karlis, Dimitris**31-45 Model-based biclustering of clickstream data***by*Melnykov, Volodymyr**46-75 Mixture-based clustering for the ordered stereotype model***by*Fernández, D. & Arnold, R. & Pledger, S.**76-85 Mixtures of spatial spline regressions for clustering and classification***by*Nguyen, Hien D. & McLachlan, Geoffrey J. & Wood, Ian A.**86-96 Wavelet-based scalar-on-function finite mixture regression models***by*Ciarleglio, Adam & Todd Ogden, R.**97-106 On the estimation of mixtures of Poisson regression models with large number of components***by*Papastamoulis, Panagiotis & Martin-Magniette, Marie-Laure & Maugis-Rabusseau, Cathy**107-118 Nonparametric estimation of species richness using discrete k-monotone distributions***by*Chee, Chew-Seng & Wang, Yong**119-130 Finite mixture of nonlinear mixed-effects joint models in the presence of missing and mismeasured covariate, with application to AIDS studies***by*Lu, Xiaosun & Huang, Yangxin & Zhu, Yiliang**131-145 General framework and model building in the class of Hidden Mixture Transition Distribution models***by*Bolano, Danilo & Berchtold, André**146-161 Latent profile analysis with nonnormal mixtures: A Monte Carlo examination of model selection using fit indices***by*Morgan, Grant B. & Hodge, Kari J. & Baggett, Aaron R.**162-176 Mixtures of quantile regressions***by*Wu, Qiang & Yao, Weixin**177-191 Laplace mixture of linear experts***by*Nguyen, Hien D. & McLachlan, Geoffrey J.**192-208 Modelling receiver operating characteristic curves using Gaussian mixtures***by*Cheam, Amay S.M. & McNicholas, Paul D.**209-227 Maximum likelihood estimation and expectation–maximization algorithm for controlled branching processes***by*González, M. & Minuesa, C. & del Puerto, I.**228-245 EM algorithms for estimating the Bernstein copula***by*Dou, Xiaoling & Kuriki, Satoshi & Lin, Gwo Dong & Richards, Donald**246-254 Transdimensional sequential Monte Carlo using variational Bayes — SMCVB***by*McGrory, C.A. & Pettitt, A.N. & Titterington, D.M. & Alston, C.L. & Kelly, M.**257-269 Partially linear transformation cure models for interval-censored data***by*Hu, Tao & Xiang, Liming**270-284 Flexible estimation in cure survival models using Bayesian P-splines***by*Bremhorst, Vincent & Lambert, Philippe**285-293 Empirical likelihood confidence regions for one- or two- samples with doubly censored data***by*Shen, Junshan & Yuen, Kam Chuen & Liu, Chunling**294-307 Nonparametric regression with doubly truncated data***by*Moreira, C. & de Uña-Álvarez, J. & Meira-Machado, L.**308-323 Parametrically guided nonparametric density and hazard estimation with censored data***by*Talamakrouni, Majda & Van Keilegom, Ingrid & El Ghouch, Anouar**324-335 The liability threshold model for censored twin data***by*Holst, Klaus K. & Scheike, Thomas H. & Hjelmborg, Jacob B.**336-347 Causal mediation analysis for survival outcome with unobserved mediator–outcome confounders***by*Luo, Peng & Geng, Zhi**348-358 Goodness-of-fit test of the stratified mark-specific proportional hazards model with continuous mark***by*Sun, Yanqing & Li, Mei & Gilbert, Peter B.**359-372 Full Bayesian inference with hazard mixture models***by*Arbel, Julyan & Lijoi, Antonio & Nipoti, Bernardo**373-387 Bayesian network data imputation with application to survival tree analysis***by*Rancoita, Paola M.V. & Zaffalon, Marco & Zucca, Emanuele & Bertoni, Francesco & de Campos, Cassio P.**390-403 Sparse estimation of high-dimensional correlation matrices***by*Cui, Ying & Leng, Chenlei & Sun, Defeng**404-420 Robust estimation of precision matrices under cellwise contamination***by*Tarr, G. & Müller, S. & Weber, N.C.**421-435 Robust groupwise least angle regression***by*Alfons, Andreas & Croux, Christophe & Gelper, Sarah**436-455 Robust tests for linear regression models based on τ-estimates***by*Salibian-Barrera, Matias & Van Aelst, Stefan & Yohai, Víctor J.**456-468 Minimum volume peeling: A robust nonparametric estimator of the multivariate mode***by*Kirschstein, T. & Liebscher, S. & Porzio, G.C. & Ragozini, G.**469-482 New upper bounds for tight and fast approximation of Fisher’s exact test in dependency rule mining***by*Hämäläinen, Wilhelmiina**483-497 Noise peeling methods to improve boosting algorithms***by*Martinez, Waldyn & Gray, J. Brian

### 2015, Volume 92, Issue C

**1-12 Fast integer-valued algorithms for optimal allocations under constraints in stratified sampling***by*Friedrich, Ulf & Münnich, Ralf & de Vries, Sven & Wagner, Matthias**13-25 Covariance matrix estimation for left-censored data***by*Pesonen, Maiju & Pesonen, Henri & Nevalainen, Jaakko**26-39 Simulation-based fully Bayesian experimental design for mixed effects models***by*Ryan, Elizabeth G. & Drovandi, Christopher C. & Pettitt, Anthony N.**40-52 Studies of the adaptive network-constrained linear regression and its application***by*Yang, Hu & Yi, Danhui**53-67 Moderately clipped LASSO***by*Kwon, Sunghoon & Lee, Sangin & Kim, Yongdai**68-83 Estimation and inference on central mean subspace for multivariate response data***by*Zhu, Liping & Zhong, Wei**84-96 Using mixtures of t densities to make inferences in the presence of missing data with a small number of multiply imputed data sets***by*Rashid, S. & Mitra, R. & Steele, R.J.**97-114 A test for equality of two distributions via jackknife empirical likelihood and characteristic functions***by*Liu, Zhi & Xia, Xiaochao & Zhou, Wang**115-125 Matrix completion discriminant analysis***by*Wu, Tong Tong & Lange, Kenneth**126-133 Detecting misspecification in the random-effects structure of cumulative logit models***by*Lin, Kuo-Chin & Chen, Yi-Ju**134-147 Regression under Cox’s model for recall-based time-to-event data in observational studies***by*Mirzaei Salehabadi, Sedigheh & Sengupta, Debasis**148-162 Nonparametric density estimation for multivariate bounded data using two non-negative multiplicative bias correction methods***by*Funke, Benedikt & Kawka, Rafael**163-176 A Bayesian mixture model to quantify parameters of spatial clustering***by*Schäfer, Martin & Radon, Yvonne & Klein, Thomas & Herrmann, Sabrina & Schwender, Holger & Verveer, Peter J. & Ickstadt, Katja

### 2015, Volume 91, Issue C

**1-3 A note on implementing the Durbin and Koopman simulation smoother***by*Jarociński, Marek**4-19 Convergent stochastic Expectation Maximization algorithm with efficient sampling in high dimension. Application to deformable template model estimation***by*Allassonnière, Stéphanie & Kuhn, Estelle**20-39 Conditional quantile estimation based on optimal quantization: From theory to practice***by*Charlier, Isabelle & Paindaveine, Davy & Saracco, Jérôme**40-50 Joint latent class model of survival and longitudinal data: An application to CPCRA study***by*Liu, Yue & Liu, Lei & Zhou, Jianhui**51-63 Long-term survival models with overdispersed number of competing causes***by*Barreto-Souza, Wagner**64-77 The hybrid method of FSIR and FSAVE for functional effective dimension reduction***by*Wang, Guochang & Zhou, Yan & Feng, Xiang-Nan & Zhang, Baoxue**78-91 Efficient maximum approximated likelihood inference for Tukey’s g-and-h distribution***by*Xu, Ganggang & Genton, Marc G.**92-101 Jackknife empirical likelihood inference for the mean absolute deviation***by*Zhao, Yichuan & Meng, Xueping & Yang, Hanfang

### 2015, Volume 90, Issue C

**1-14 Data augmentation and parameter expansion for independent or spatially correlated ordinal data***by*Schliep, Erin M. & Hoeting, Jennifer A.**15-35 Grouped variable importance with random forests and application to multiple functional data analysis***by*Gregorutti, Baptiste & Michel, Bertrand & Saint-Pierre, Philippe**36-46 Finding Dantzig selectors with a proximity operator based fixed-point algorithm***by*Prater, Ashley & Shen, Lixin & Suter, Bruce W.**47-60 Robust and efficient estimation of effective dose***by*Karunamuni, Rohana J. & Tang, Qingguo & Zhao, Bangxin**61-73 Location and scale mixtures of Gaussians with flexible tail behaviour: Properties, inference and application to multivariate clustering***by*Wraith, Darren & Forbes, Florence**74-83 Sparse HDLSS discrimination with constrained data piling***by*Ahn, Jeongyoun & Jeon, Yongho**84-99 Improved methods for the imputation of missing data by nearest neighbor methods***by*Tutz, Gerhard & Ramzan, Shahla**100-113 Tests of exponentiality based on Arnold–Villasenor characterization and their efficiencies***by*Jovanović, Milan & Milošević, Bojana & Nikitin, Ya. Yu. & Obradović, Marko & Volkova, K. Yu.**114-131 Kernel Generalized Canonical Correlation Analysis***by*Tenenhaus, Arthur & Philippe, Cathy & Frouin, Vincent

### 2015, Volume 89, Issue C

**1-11 Modeling sleep fragmentation in sleep hypnograms: An instance of fast, scalable discrete-state, discrete-time analyses***by*Swihart, Bruce J. & Punjabi, Naresh M. & Crainiceanu, Ciprian M.**12-24 Variational algorithms for biclustering models***by*Vu, Duy & Aitkin, Murray**25-38 An adaptive test for the mean vector in large-p-small-n problems***by*Shen, Yanfeng & Lin, Zhengyan**39-50 A semiparametric additive rates model for multivariate recurrent events with missing event categories***by*Ye, Peng & Zhao, Xingqiu & Sun, Liuquan & Xu, Wei**51-71 Improving cross-validated bandwidth selection using subsampling-extrapolation techniques***by*Wang, Qing & Lindsay, Bruce G.**72-84 Non-parametric entropy estimators based on simple linear regression***by*Hino, Hideitsu & Koshijima, Kensuke & Murata, Noboru**85-96 Estimation for mixed exponential distributions under type-II progressively hybrid censored samples***by*Tian, Yuzhu & Zhu, Qianqian & Tian, Maozai**97-114 Generalized endpoint-inflated binomial model***by*Tian, Guo-Liang & Ma, Huijuan & Zhou, Yong & Deng, Dianliang**115-125 Behavior of EWMA type control charts for small smoothing parameters***by*Lazariv, Taras & Okhrin, Yarema & Schmid, Wolfgang**126-133 Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models***by*Yue, Chen & Chen, Shaojie & Sair, Haris I. & Airan, Raag & Caffo, Brian S.**134-146 An adaptive minimum spanning tree test for detecting irregularly-shaped spatial clusters***by*Zhou, Ruoyu & Shu, Lianjie & Su, Yan**147-157 A random-effect model approach for group variable selection***by*Lee, Sangin & Pawitan, Yudi & Lee, Youngjo**158-171 Likelihood inference for small area estimation using data cloning***by*Torabi, Mahmoud & Lele, Subhash R. & Prasad, Narasimha G.N.**172-191 Fast goodness-of-fit tests based on the characteristic function***by*Jiménez-Gamero, M. Dolores & Kim, Hyoung-Moon**192-203 Sparse principal component regression with adaptive loading***by*Kawano, Shuichi & Fujisawa, Hironori & Takada, Toyoyuki & Shiroishi, Toshihiko**204-221 Orthogonality-projection-based estimation for semi-varying coefficient models with heteroscedastic errors***by*Zhao, Yan-Yong & Lin, Jin-Guan & Xu, Pei-Rong & Ye, Xu-Guo**222-244 Bayesian nonparametric estimation of test equating functions with covariates***by*González, Jorge & Barrientos, Andrés F. & Quintana, Fernando A.

### 2015, Volume 88, Issue C

**1-14 Local linear estimation of residual entropy function of conditional distributions***by*Rajesh, G. & Abdul-Sathar, E.I. & Maya, R.**15-27 Two simple algorithms on linear combination of multiple biomarkers to maximize partial area under the ROC curve***by*Yu, Wenbao & Park, Taesung**28-39 Comorbidity of chronic diseases in the elderly: Patterns identified by a copula design for mixed responses***by*Stöber, Jakob & Hong, Hyokyoung Grace & Czado, Claudia & Ghosh, Pulak**40-52 Modelling discrete longitudinal data using acyclic probabilistic finite automata***by*Ankinakatte, Smitha & Edwards, David**53-74 Unbiased regression trees for longitudinal and clustered data***by*Fu, Wei & Simonoff, Jeffrey S.**75-99 SIMD parallel MCMC sampling with applications for big-data Bayesian analytics***by*Mahani, Alireza S. & Sharabiani, Mansour T.A.**100-110 Nested nonnegative cone analysis***by*Zhang, Lingsong & Lu, Shu & Marron, J.S.**111-118 Best linear near unbiased estimation for nonlinear signal models via semi-infinite programming approach***by*Ling, Bingo Wing-Kuen & Ho, Charlotte Yuk-Fan & Siu, Wan-Chi & Dai, Qingyun**119-127 Generalized orthogonal components regression for high dimensional generalized linear models***by*Lin, Yanzhu & Zhang, Min & Zhang, Dabao**128-138 A lack-of-fit test for quantile regression models with high-dimensional covariates***by*Conde-Amboage, Mercedes & Sánchez-Sellero, César & González-Manteiga, Wenceslao**139-153 Mixture model selection via hierarchical BIC***by*Zhao, Jianhua & Jin, Libin & Shi, Lei**154-172 Quantile regression methods with varying-coefficient models for censored data***by*Xie, Shangyu & Wan, Alan T.K. & Zhou, Yong**173-186 Multilevel cumulative logistic regression model with random effects: Application to British social attitudes panel survey data***by*Chan, Moon-tong & Yu, Dalei & Yau, Kelvin K.W.**187-207 On second order efficient robust inference***by*Paul, Subhadeep & Basu, Ayanendranath

### 2015, Volume 87, Issue C

**1-17 Kappa statistic for clustered physician–patients polytomous data***by*Yang, Zhao & Zhou, Ming**18-33 A case-deletion diagnostic for penalized calibration estimators and BLUP under linear mixed models in survey sampling***by*Barranco-Chamorro, I. & Jiménez-Gamero, M.D. & Mayor-Gallego, J.A. & Moreno-Rebollo, J.L.**34-45 Regression analysis of multivariate current status data with auxiliary covariates under the additive hazards model***by*Chen, Yurong & Feng, Yanqin & Sun, Jianguo**46-56 A new estimating equation approach for marginal hazard ratio estimation***by*Niu, Yi & Peng, Yingwei**57-72 Faithfulness and learning hypergraphs from discrete distributions***by*Klimova, Anna & Uhler, Caroline & Rudas, Tamás**73-83 A Bayesian hierarchical model for estimating and partitioning Bernstein polynomial density functions***by*Gard, Charlotte C. & Brown, Elizabeth R.**84-101 Model based clustering of high-dimensional binary data***by*Tang, Yang & Browne, Ryan P. & McNicholas, Paul D.**102-115 Archetypoids: A new approach to define representative archetypal data***by*Vinué, Guillermo & Epifanio, Irene & Alemany, Sandra**116-135 Adjusted quasi-maximum likelihood estimator for mixed regressive, spatial autoregressive model and its small sample bias***by*Yu, Dalei & Bai, Peng & Ding, Chang

### 2015, Volume 86, Issue C

**1-12 Entropy test and residual empirical process for autoregressive conditional duration models***by*Lee, Sangyeol & Oh, Haejune**13-26 The dual and degrees of freedom of linearly constrained generalized lasso***by*Hu, Qinqin & Zeng, Peng & Lin, Lu**27-41 An external field prior for the hidden Potts model with application to cone-beam computed tomography***by*Moores, Matthew T. & Hargrave, Catriona E. & Deegan, Timothy & Poulsen, Michael & Harden, Fiona & Mengersen, Kerrie**42-51 Multiple comparisons for survival data with propensity score adjustment***by*Zhu, Hong & Lu, Bo**52-64 Anatomical curve identification***by*Bowman, Adrian W. & Katina, Stanislav & Smith, Joanna & Brown, Denise**65-80 Tree-based varying coefficient regression for longitudinal ordinal responses***by*Bürgin, Reto & Ritschard, Gilbert**81-96 Bayesian estimation of a discrete response model with double rules of sample selection***by*Zhang, Rong & Inder, Brett A. & Zhang, Xibin**97-110 Transdimensional approximate Bayesian computation for inference on invasive species models with latent variables of unknown dimension***by*Chkrebtii, Oksana A. & Cameron, Erin K. & Campbell, David A. & Bayne, Erin M.

### 2015, Volume 85, Issue C

**1-22 Robust nonnegative garrote variable selection in linear regression***by*Gijbels, I. & Vrinssen, I.**23-36 The cluster graphical lasso for improved estimation of Gaussian graphical models***by*Tan, Kean Ming & Witten, Daniela & Shojaie, Ali**37-53 A fast EM algorithm for fitting joint models of a binary response and multiple longitudinal covariates subject to detection limits***by*Bernhardt, Paul W. & Zhang, Daowen & Wang, Huixia Judy**54-66 GEE type inference for clustered zero-inflated negative binomial regression with application to dental caries***by*Kong, Maiying & Xu, Sheng & Levy, Steven M. & Datta, Somnath**67-83 Sample size methods for constructing confidence intervals for the intra-class correlation coefficient***by*Dobbin, Kevin K. & Ionan, Alexei C.**84-99 Bayesian threshold selection for extremal models using measures of surprise***by*Lee, J. & Fan, Y. & Sisson, S.A.

### 2015, Volume 84, Issue C

**1-13 Nonparametric estimation of pair-copula constructions with the empirical pair-copula***by*Hobæk Haff, Ingrid & Segers, Johan**14-26 Approximate maximum likelihood estimation of the autologistic model***by*Bee, Marco & Espa, Giuseppe & Giuliani, Diego**27-40 An exact polynomial time algorithm for computing the least trimmed squares estimate***by*Klouda, Karel**41-53 A Gaussian pseudolikelihood approach for quantile regression with repeated measurements***by*Fu, Liya & Wang, You-Gan & Zhu, Min**54-67 A penalized simulated maximum likelihood approach in parameter estimation for stochastic differential equations***by*Sun, Libo & Lee, Chihoon & Hoeting, Jennifer A.**68-84 Iterated Bernstein operators for distribution function and density estimation: Balancing between the number of iterations and the polynomial degree***by*Manté, Claude**85-98 A pseudo-likelihood approach for estimating diagnostic accuracy of multiple binary medical tests***by*Liu, Wei & Zhang, Bo & Zhang, Zhiwei & Chen, Baojiang & Zhou, Xiao-Hua**99-115 A semiparametric Bayesian approach for joint-quantile regression with clustered data***by*Jang, Woosung & Wang, Huixia Judy**116-134 Confidence interval construction for the Youden index based on partially validated series***by*Poon, Wai-Yin & Qiu, Shi-Fang & Tang, Man-Lai**135-151 A new MM algorithm for constrained estimation in the proportional hazards model***by*Ding, Jieli & Tian, Guo-Liang & Yuen, Kam Chuen

### 2015, Volume 83, Issue C

**1-13 Accurate ensemble pruning with PL-bagging***by*Chung, Dongjun & Kim, Hyunjoong**14-25 Stationary bootstrapping for semiparametric panel unit root tests***by*Hwang, Eunju & Shin, Dong Wan**26-36 Inference on the Weibull distribution based on record values***by*Wang, Bing Xing & Ye, Zhi-Sheng**37-51 Prediction intervals for integrals of Gaussian random fields***by*De Oliveira, Victor & Kone, Bazoumana**52-64 Checking the adequacy for a distortion errors-in-variables parametric regression model***by*Zhang, Jun & Li, Gaorong & Feng, Zhenghui