# Elsevier

# Computational Statistics & Data Analysis

**Download restrictions:**Full text for ScienceDirect subscribers only.

**Editor:**

**For corrections or technical questions regarding this series, please contact (Dana Niculescu)**

**Series handle:**repec:eee:csdana

**ISSN:**0167-9473

**Citations RSS feed:**at CitEc

### Impact factors

- Simple (last 10 years)
- Recursive (10)
- Discounted (10)
- Recursive discounted (10)
- H-Index (10)
- Euclid (10)
- Aggregate (10)

**Access and download statistics**

**Top item:**

- By citations
- By downloads (last 12 months)

### 2017, Volume 105, Issue C

**11-23 Quasi-systematic sampling from a continuous population***by*Wilhelm, Matthieu & Tillé, Yves & Qualité, Lionel**24-45 Depth-based nonparametric description of functional data, with emphasis on use of spatial depth***by*Serfling, Robert & Wijesuriya, Uditha**46-52 A note on modeling sparse exponential-family functional response curves***by*Gertheiss, Jan & Goldsmith, Jeff & Staicu, Ana-Maria**53-58 A fast algorithm for two-dimensional Kolmogorov–Smirnov two sample tests***by*Xiao, Yuanhui**59-75 Fitting large-scale structured additive regression models using Krylov subspace methods***by*Schmidt, Paul & Mühlau, Mark & Schmid, Volker**76-95 A general hidden state random walk model for animal movement***by*Nicosia, Aurélien & Duchesne, Thierry & Rivest, Louis-Paul & Fortin, Daniel**96-111 Normal–Gamma–Bernoulli peak detection for analysis of comprehensive two-dimensional gas chromatography mass spectrometry data***by*Kim, Seongho & Jang, Hyejeong & Koo, Imhoi & Lee, Joohyoung & Zhang, Xiang**112-124 Confidence intervals through sequential Monte Carlo***by*Silva, Ivair R.**125-143 Asymptotically optimal differenced estimators of error variance in nonparametric regression***by*Wang, WenWu & Yu, Ping**144-165 Nonparametric incidence estimation and bootstrap bandwidth selection in mixture cure models***by*López-Cheda, Ana & Cao, Ricardo & Jácome, M. Amalia & Van Keilegom, Ingrid**166-183 Approximate maximum likelihood estimation using data-cloning ABC***by*Picchini, Umberto & Anderson, Rachele**184-200 Bayesian local influence analysis of general estimating equations with nonignorable missing data***by*Zhang, Yan-Qing & Tang, Nian-Sheng**201-216 Model free feature screening for ultrahigh dimensional data with responses missing at random***by*Lai, Peng & Liu, Yiming & Liu, Zhi & Wan, Yi**217-228 A simple approach to sparse clustering***by*Arias-Castro, Ery & Pu, Xiao**229-242 Rank constrained distribution and moment computations***by*Kiatsupaibul, Seksan & J. Hayter, Anthony & Liu, Wei**243-267 Robust estimation in stochastic frontier models***by*Song, Junmo & Oh, Dong-hyun & Kang, Jiwon**268-279 Sequential rank CUSUM charts for angular data***by*Lombard, F. & Hawkins, Douglas M. & Potgieter, Cornelis J.**280-292 Data-driven algorithms for dimension reduction in causal inference***by*Persson, Emma & Häggström, Jenny & Waernbaum, Ingeborg & de Luna, Xavier

### 2016, Volume 104, Issue C

**1-9 A distribution-free m-out-of-n bootstrap approach to testing symmetry about an unknown median***by*Lyubchich, Vyacheslav & Wang, Xingyu & Heyes, Andrew & Gel, Yulia R.**10-23 Power computation for hypothesis testing with high-dimensional covariance matrices***by*Lin, Ruitao & Liu, Zhongying & Zheng, Shurong & Yin, Guosheng**24-34 Functional archetype and archetypoid analysis***by*Epifanio, Irene**35-50 Bayesian crossover designs for generalized linear models***by*Singh, Satya Prakash & Mukhopadhyay, Siuli**51-65 Visualizing the effects of a changing distance on data using continuous embeddings***by*Gruenhage, Gina & Opper, Manfred & Barthelme, Simon**66-78 Integrative weighted group lasso and generalized local quadratic approximation***by*Pan, Qing & Zhao, Yunpeng**79-90 Partial identification in the statistical matching problem***by*Ahfock, Daniel & Pyne, Saumyadipta & Lee, Sharon X. & McLachlan, Geoffrey J.**91-109 n-consistent density estimation in semiparametric regression models***by*Li, Shuo & Tu, Yundong**110-129 Semi-parametric copula sample selection models for count responses***by*Marra, Giampiero & Wyszynski, Karol**130-147 Smoothed stationary bootstrap bandwidth selection for density estimation with dependent data***by*Barbeito, Inés & Cao, Ricardo**148-168 Bayesian estimation of the tail index of a heavy tailed distribution under random censoring***by*Ameraoui, Abdelkader & Boukhetala, Kamal & Dupuy, Jean-François**169-182 Estimating random-intercept models on data streams***by*Ippel, L. & Kaptein, M.C. & Vermunt, J.K.**183-196 Using the Bayesian Shtarkov solution for predictions***by*Le, Tri & Clarke, Bertrand**197-208 Cause-specific hazard regression for competing risks data under interval censoring and left truncation***by*Li, Chenxi**209-222 Robust methods for heteroskedastic regression***by*Atkinson, Anthony C. & Riani, Marco & Torti, Francesca**223-232 Multiple comparisons of treatments with skewed ordinal responses***by*Lu, Tong-Yu & Poon, Wai-Yin & Cheung, Siu Hung**233-246 Modeling nonstationary covariance function with convolution on sphere***by*Li, Yang & Zhu, Zhengyuan

### 2016, Volume 103, Issue C

**1-16 Nonparametric mixture models with conditionally independent multivariate component densities***by*Chauveau, Didier & Hoang, Vy Thuy Lynh**17-27 On a dispersion model with Pearson residual responses***by*Wu, K.Y.K. & Li, W.K.**28-55 Copula in a multivariate mixed discrete–continuous model***by*Zilko, Aurelius A. & Kurowicka, Dorota**56-67 Bandwidth selection for kernel log-density estimation***by*Hazelton, Martin L. & Cox, Murray P.**68-78 Bayesian model selection in ordinal quantile regression***by*Alhamzawi, Rahim**79-90 Cox regression analysis of dependent interval-censored failure time data***by*Ma, Ling & Hu, Tao & Sun, Jianguo**91-110 Multidimensional and longitudinal item response models for non-ignorable data***by*Santos, Vera Lúcia F. & Moura, Fernando A.S. & Andrade, Dalton F. & Gonçalves, Kelly C.M.**111-123 Iterated imputation estimation for generalized linear models with missing response and covariate values***by*Fang, Fang & Shao, Jun**124-138 A covariate nonrandomized response model for multicategorical sensitive variables***by*Groenitz, Heiko**139-150 Reduced rank regression with possibly non-smooth criterion functions: An empirical likelihood approach***by*Feng, Sanying & Lian, Heng & Zhu, Fukang**151-169 Linear mixed models with marginally symmetric nonparametric random effects***by*Nguyen, Hien D. & McLachlan, Geoffrey J.**170-192 Confidence intervals for an ordinal effect size measure based on partially validated series***by*Qiu, Shi-Fang & Poon, Wai-Yin & Tang, Man-Lai**193-205 Ensemble sufficient dimension folding methods for analyzing matrix-valued data***by*Xue, Yuan & Yin, Xiangrong & Jiang, Xiaolin**206-228 A variational Expectation–Maximization algorithm for temporal data clustering***by*El Assaad, Hani & Samé, Allou & Govaert, Gérard & Aknin, Patrice**229-241 Functional regression approximate Bayesian computation for Gaussian process density estimation***by*Rodrigues, G.S. & Nott, David J. & Sisson, S.A.**242-249 A multiple imputation approach to the analysis of clustered interval-censored failure time data with the additive hazards model***by*Chen, Ling & Sun, Jianguo & Xiong, Chengjie**250-262 A relative error-based approach for variable selection***by*Hao, Meiling & Lin, Yunyuan & Zhao, Xingqiu**263-283 Heteroscedasticity testing for regression models: A dimension reduction-based model adaptive approach***by*Zhu, Xuehu & Chen, Fei & Guo, Xu & Zhu, Lixing**284-303 Ridge estimation of inverse covariance matrices from high-dimensional data***by*van Wieringen, Wessel N. & Peeters, Carel F.W.**304-315 Tolerance limits under normal mixtures: Application to the evaluation of nuclear power plant safety and to the assessment of circular error probable***by*Zimmer, Zachary & Park, DoHwan & Mathew, Thomas**316-329 A flexible approach to inference in semiparametric regression models with correlated errors using Gaussian processes***by*He, Heping & Severini, Thomas A.**330-349 Adaptive spectral estimation for nonstationary multivariate time series***by*Zhang, Shibin**350-366 Comparing classical criteria for selecting intra-class correlated features in Multimix***by*Hunt, Lynette A. & Basford, Kaye E.**367-383 Gaussian process hyper-parameter estimation using Parallel Asymptotically Independent Markov Sampling***by*Garbuno-Inigo, A. & DiazDelaO, F.A. & Zuev, K.M.**384-400 Robust shrinkage estimation and selection for functional multiple linear model through LAD loss***by*Huang, Lele & Zhao, Junlong & Wang, Huiwen & Wang, Siyang**401-412 The use of random-effect models for high-dimensional variable selection problems***by*Kwon, Sunghoon & Oh, Seungyoung & Lee, Youngjo**413-425 Semiparametric mixture: Continuous scale mixture approach***by*Xiang, Sijia & Yao, Weixin & Seo, Byungtae**426-437 Efficient computation of the quasi likelihood function for discretely observed diffusion processes***by*Höök, Lars Josef & Lindström, Erik

### 2016, Volume 102, Issue C

**1-22 Estimation of linear target-layer trajectories using cluttered point cloud data***by*Bryner, Darshan & Huffer, Fred & Rosenthal, Michael & Tucker, J. Derek & Srivastava, Anuj**23-36 Maximum likelihood estimation of triangular and polygonal distributions***by*Nguyen, Hien D. & McLachlan, Geoffrey J.**37-54 A simple testing procedure for unit root and model specification***by*Costantini, Mauro & Sen, Amit**55-66 Improved near-exact distributions for the product of independent Generalized Gamma random variables***by*Marques, Filipe J. & Loingeville, Florence**67-84 On bandwidth selection using minimal spanning tree for kernel density estimation***by*Sreevani, & Murthy, C.A.**85-97 Feature screening for generalized varying coefficient models with application to dichotomous responses***by*Xia, Xiaochao & Yang, Hu & Li, Jialiang**98-109 A new nested Cholesky decomposition and estimation for the covariance matrix of bivariate longitudinal data***by*Feng, Sanying & Lian, Heng & Xue, Liugen

### 2016, Volume 101, Issue C

**1-11 EM algorithm in Gaussian copula with missing data***by*Ding, Wei & Song, Peter X.-K.**12-28 Symmetric adaptive smoothing regimens for estimation of the spatial relative risk function***by*Davies, Tilman M. & Jones, Khair & Hazelton, Martin L.**29-43 Inference and mixture modeling with the Elliptical Gamma Distribution***by*Hosseini, Reshad & Sra, Suvrit & Theis, Lucas & Bethge, Matthias**44-56 Computation of the autocovariances for time series with multiple long-range persistencies***by*McElroy, Tucker S. & Holan, Scott H.**57-63 Covariate-adjusted quantile inference with competing risks***by*Lee, Minjung & Han, Junhee**64-79 Bayesian nonparametric multiple testing***by*Cipolli III, William & Hanson, Timothy & McLain, Alexander C.**80-92 Change of spatiotemporal scale in dynamic models***by*Kim, Yongku & Berliner, L. Mark**93-109 Dynamic GSCANO (Generalized Structured Canonical Correlation Analysis) with applications to the analysis of effective connectivity in functional neuroimaging data***by*Zhou, Lixing & Takane, Yoshio & Hwang, Heungsun**110-120 Prior selection for panel vector autoregressions***by*Korobilis, Dimitris**121-136 A Bayesian method for simultaneous registration and clustering of functional observations***by*Wu, Zizhen & Hitchcock, David B.**137-147 Maximum likelihood estimation of the mixture of log-concave densities***by*Hu, Hao & Wu, Yichao & Yao, Weixin**148-160 A fast and objective multidimensional kernel density estimation method: fastKDE***by*O’Brien, Travis A. & Kashinath, Karthik & Cavanaugh, Nicholas R. & Collins, William D. & O’Brien, John P.**161-173 Multivariate frailty models for multi-type recurrent event data and its application to cancer prevention trial***by*Bedair, Khaled & Hong, Yili & Li, Jie & Al-Khalidi, Hussein R.**174-185 Using link-preserving imputation for logistic partially linear models with missing covariates***by*Chen, Qixuan & Paik, Myunghee Cho & Kim, Minjin & Wang, Cuiling**186-208 Structure learning in Bayesian Networks using regular vines***by*Hobæk Haff, Ingrid & Aas, Kjersti & Frigessi, Arnoldo & Lacal, Virginia**209-225 Robust closed-form estimators for the integer-valued GARCH (1,1) model***by*Li, Qi & Lian, Heng & Zhu, Fukang**226-235 Data Shared Lasso: A novel tool to discover uplift***by*Gross, Samuel M. & Tibshirani, Robert**236-249 Random density functions with common atoms and pairwise dependence***by*Hatjispyros, Spyridon J. & Nicoleris, Theodoros & Walker, Stephen G.**250-276 Bayes shrinkage estimation for high-dimensional VAR models with scale mixture of normal distributions for noise***by*Lee, Namgil & Choi, Hyemi & Kim, Sung-Ho**277-288 High resolution simulation of nonstationary Gaussian random fields***by*Kleiber, William**289-299 l1 regularized multiplicative iterative path algorithm for non-negative generalized linear models***by*Mandal, B.N. & Ma, Jun**300-315 Accurate pairwise convolutions of non-negative vectors via FFT***by*Wilson, Huon & Keich, Uri

### 2016, Volume 100, Issue C

**4-16 Spectral approach to parameter-free unit root testing***by*Bailey, Natalia & Giraitis, Liudas**17-36 Estimation and empirical performance of non-scalar dynamic conditional correlation models***by*Bauwens, Luc & Grigoryeva, Lyudmila & Ortega, Juan-Pablo**37-57 Efficient Gibbs sampling for Markov switching GARCH models***by*Billio, Monica & Casarin, Roberto & Osuntuyi, Anthony**58-69 Semiparametric score driven volatility models***by*Blasques, Francisco & Ji, Jiangyu & Lucas, André**70-78 Bayesian nonparametric forecasting for INAR models***by*Bisaglia, Luisa & Canale, Antonio**79-98 Predicting the yield curve using forecast combinations***by*Caldeira, João F. & Moura, Guilherme V. & Santos, André A.P.**99-114 On selection of statistics for approximate Bayesian computing (or the method of simulated moments)***by*Creel, Michael & Kristensen, Dennis**115-130 State space modeling of Gegenbauer processes with long memory***by*Dissanayake, G.S. & Peiris, M.S. & Proietti, T.**131-152 Managing risk with a realized copula parameter***by*Fengler, Matthias R. & Okhrin, Ostap**153-159 Skewness and kurtosis of multivariate Markov-switching processes***by*Fiorentini, Gabriele & Planas, Christophe & Rossi, Alessandro**160-169 A simple test for a bubble based on growth and acceleration***by*Franses, Philip Hans**170-185 The uncertainty of conditional returns, volatilities and correlations in DCC models***by*Fresoli, Diego E. & Ruiz, Esther**186-204 The ability to correct the bias in the stable AD(1,1) model with a feedback effect***by*van Giersbergen, Noud P.A.**205-220 On the computation of multivariate scenario sets for the skew-t and generalized hyperbolic families***by*Giorgi, Emanuele & McNeil, Alexander J.**221-239 Revisiting useful approaches to data-rich macroeconomic forecasting***by*Groen, Jan J.J. & Kapetanios, George**240-264 Improved GMM estimation of panel VAR models***by*Hayakawa, Kazuhiko**265-303 On the behaviour of the GMM estimator in persistent dynamic panel data models with unrestricted initial conditions***by*Hayakawa, Kazuhiko & Nagata, Shuichi**304-317 On conditional covariance modelling: An approach using state space models***by*Hendrych, R. & Cipra, T.**318-330 Testing for the number of states in hidden Markov models***by*Holzmann, Hajo & Schwaiger, Florian**331-350 Matrix exponential stochastic volatility with cross leverage***by*Ishihara, Tsunehiro & Omori, Yasuhiro & Asai, Manabu**351-368 Asymmetry in tail dependence in equity portfolios***by*Jondeau, Eric**369-382 Forecasting inflation and GDP growth using heuristic optimisation of information criteria and variable reduction methods***by*Kapetanios, George & Marcellino, Massimiliano & Papailias, Fotis**383-400 Testing for jumps in conditionally Gaussian ARMA–GARCH models, a robust approach***by*Laurent, Sébastien & Lecourt, Christelle & Palm, Franz C.**401-423 Semiparametric GMM estimation and variable selection in dynamic panel data models with fixed effects***by*Li, Rui & Wan, Alan T.K. & You, Jinhong**424-444 Generalized nonparametric smoothing with mixed discrete and continuous data***by*Li, Degui & Simar, Léopold & Zelenyuk, Valentin**445-466 Horizon effect in the term structure of long-run risk-return trade-offs***by*Okou, Cédric & Jacquier, Éric**467-494 Bootstrap prediction intervals for Markov processes***by*Pan, Li & Politis, Dimitris N.**495-511 The Fisher effect in the presence of time-varying coefficients***by*Panopoulou, Ekaterini & Pantelidis, Theologos**512-525 A simple and successful shrinkage method for weighting estimators of treatment effects***by*Pohlmeier, Winfried & Seiberlich, Ruben & Uysal, Selver Derya**526-544 Neighbourhood GMM estimation of dynamic panel data models***by*Sarafidis, Vasilis**545-559 Confidence intervals for ARMA–GARCH Value-at-Risk: The case of heavy tails and skewness***by*Spierdijk, Laura**560-581 The Split-SV model***by*Stojanović, Vladica S. & Popović, Biljana Č. & Milovanović, Gradimir V.**582-594 Estimation and inference in univariate and multivariate log-GARCH-X models when the conditional density is unknown***by*Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro**595-615 Linking Tukey’s legacy to financial risk measurement***by*Vijverberg, Chu-Ping C. & Vijverberg, Wim P.M. & Taşpınar, Süleyman**616-630 Bayesian model selection for unit root testing with multiple structural breaks***by*Vosseler, Alexander**633-644 The exact Gaussian likelihood estimation of time-dependent VARMA models***by*Alj, Abdelkamel & Jónasson, Kristján & Mélard, Guy**645-660 A bootstrap approximation for the distribution of the Local Whittle estimator***by*Arteche, Josu & Orbe, Jesus**661-675 Real-time factor model forecasting and the effects of instability***by*Clements, Michael P.**676-693 Adaptive bandwidth selection in the long run covariance estimator of functional time series***by*Horváth, Lajos & Rice, Gregory & Whipple, Stephen**694-711 Interval-valued time series models: Estimation based on order statistics exploring the Agriculture Marketing Service data***by*Lin, Wei & González-Rivera, Gloria**712-733 Moment Ratio estimation of autoregressive/unit root parameters and autocorrelation-consistent standard errors***by*McCulloch, J. Huston**734-762 Approximating and reducing bias in 2SLS estimation of dynamic simultaneous equation models***by*Phillips, Garry D.A. & Liu-Evans, Gareth**763-772 A Gini-based unit root test***by*Shelef, Amit**773-793 Iteratively reweighted adaptive lasso for conditional heteroscedastic time series with applications to AR–ARCH type processes***by*Ziel, Florian**795-813 Dynamic equicorrelation stochastic volatility***by*Kurose, Yuta & Omori, Yasuhiro**814-829 A Bayesian non-parametric approach to asymmetric dynamic conditional correlation model with application to portfolio selection***by*Virbickaitė, Audronė & Ausín, M. Concepción & Galeano, Pedro**830-846 Income inequality decomposition using a finite mixture of log-normal distributions: A Bayesian approach***by*Lubrano, Michel & Ndoye, Abdoul Aziz Junior**847-859 Fast computation of the deviance information criterion for latent variable models***by*Chan, Joshua C.C. & Grant, Angelia L.

### 2016, Volume 99, Issue C

**1-11 Robust regression estimation and inference in the presence of cellwise and casewise contamination***by*Leung, Andy & Zhang, Hongyang & Zamar, Ruben**12-24 Identification of proportionality structure with two-part models using penalization***by*Fang, Kuangnan & Wang, Xiaoyan & Shia, Ben-Chang & Ma, Shuangge**25-37 Testing hypothesis for a simple ordering in incomplete contingency tables***by*Li, Hui-Qiong & Tian, Guo-Liang & Jiang, Xue-Jun & Tang, Nian-Sheng**38-50 Bayesian inference of Weibull distribution based on left truncated and right censored data***by*Kundu, Debasis & Mitra, Debanjan**51-67 Generalized Poisson autoregressive models for time series of counts***by*Chen, Cathy W.S. & Lee, Sangyeol**68-80 A flexible zero-inflated model to address data dispersion***by*Sellers, Kimberly F. & Raim, Andrew**81-90 General sparse multi-class linear discriminant analysis***by*Safo, Sandra E. & Ahn, Jeongyoun**91-104 A generalized likelihood ratio test for normal mean when p is greater than n***by*Zhao, Junguang & Xu, Xingzhong**105-114 A multiple imputation approach for semiparametric cure model with interval censored data***by*Zhou, Jie & Zhang, Jiajia & McLain, Alexander C. & Cai, Bo**115-130 On point estimation of the abnormality of a Mahalanobis index***by*Elfadaly, Fadlalla G. & Garthwaite, Paul H. & Crawford, John R.**131-147 The joint role of trimming and constraints in robust estimation for mixtures of Gaussian factor analyzers***by*García-Escudero, Luis Angel & Gordaliza, Alfonso & Greselin, Francesca & Ingrassia, Salvatore & Mayo-Iscar, Agustín**148-170 A practical approximation algorithm for the LTS estimator***by*Mount, David M. & Netanyahu, Nathan S. & Piatko, Christine D. & Wu, Angela Y. & Silverman, Ruth**171-188 SMILE: A novel dissimilarity-based procedure for detecting sparse-specific profiles in sparse contingency tables***by*Emily, Mathieu & Hitte, Christophe & Mom, Alain**189-203 A new method for simultaneous estimation of the factor model parameters, factor scores, and unique parts***by*Stegeman, Alwin**204-222 Classification methods for Hilbert data based on surrogate density***by*Bongiorno, Enea G. & Goia, Aldo**223-234 Small area estimation of the Gini concentration coefficient***by*Fabrizi, Enrico & Trivisano, Carlo**235-247 On Liu’s simplicial depth and Randles’ interdirections***by*Serfling, Robert & Wang, Yunfei

### 2016, Volume 98, Issue C

**1-18 Sparse Tucker2 analysis of three-way data subject to a constrained number of zero elements in a core array***by*Ikemoto, Hiroki & Adachi, Kohei**19-30 Exact computation of the halfspace depth***by*Dyckerhoff, Rainer & Mozharovskyi, Pavlo**31-45 Destructive weighted Poisson cure rate models with bivariate random effects: Classical and Bayesian approaches***by*Gallardo, Diego I. & Bolfarine, Heleno & Pedroso-de-Lima, Antonio Carlos**46-59 High dimensional classifiers in the imbalanced case***by*Bak, Britta Anker & Jensen, Jens Ledet**60-70 A powerful FDR control procedure for multiple hypotheses***by*Zhao, Haibing & Fung, Wing Kam**71-78 Regression correlation coefficient for a Poisson regression model***by*Takahashi, Akihito & Kurosawa, Takeshi**79-90 Using hierarchical centering to facilitate a reversible jump MCMC algorithm for random effects models***by*Oedekoven, C.S. & King, R. & Buckland, S.T. & Mackenzie, M.L. & Evans, K.O. & Burger, L.W.**91-104 Estimating extreme tail risk measures with generalized Pareto distribution***by*Park, Myung Hyun & Kim, Joseph H.T.

### 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