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ORCIDComputational Statistics & Data Analysis, Volume 103
Volume 103, November 2016
- Didier Chauveau, Vy Thuy Lynh Hoang
:
Nonparametric mixture models with conditionally independent multivariate component densities. 1-16
- K. Y. K. Wu, W. K. Li:
On a dispersion model with Pearson residual responses. 17-27 - Aurelius A. Zilko, Dorota Kurowicka:
Copula in a multivariate mixed discrete-continuous model. 28-55 - Martin L. Hazelton, Murray P. Cox:
Bandwidth selection for kernel log-density estimation. 56-67 - Rahim Alhamzawi:
Bayesian model selection in ordinal quantile regression. 68-78 - Ling Ma, Tao Hu, Jianguo Sun:
Cox regression analysis of dependent interval-censored failure time data. 79-90 - Vera Lúcia F. Santos, Fernando A. S. Moura, Dalton F. Andrade, Kelly C. M. Gonçalves:
Multidimensional and longitudinal item response models for non-ignorable data. 91-110
- Fang Fang, Jun Shao:
Iterated imputation estimation for generalized linear models with missing response and covariate values. 111-123
- Heiko Groenitz:
A covariate nonrandomized response model for multicategorical sensitive variables. 124-138 - Sanying Feng, Heng Lian, Fukang Zhu:
Reduced rank regression with possibly non-smooth criterion functions: An empirical likelihood approach. 139-150
- Hien Duy Nguyen, Geoffrey J. McLachlan:
Linear mixed models with marginally symmetric nonparametric random effects. 151-169
- Shi-Fang Qiu, Wai-Yin Poon, Man-Lai Tang:
Confidence intervals for an ordinal effect size measure based on partially validated series. 170-192 - Yuan Xue, Xiangrong Yin, Xiaolin Jiang:
Ensemble sufficient dimension folding methods for analyzing matrix-valued data. 193-205 - Hani El Assaad, Allou Samé, Gérard Govaert, Patrice Aknin:
A variational Expectation-Maximization algorithm for temporal data clustering. 206-228 - G. S. Rodrigues, David J. Nott, Scott A. Sisson:
Functional regression approximate Bayesian computation for Gaussian process density estimation. 229-241 - Ling Chen, Jianguo Sun, Chengjie Xiong:
A multiple imputation approach to the analysis of clustered interval-censored failure time data with the additive hazards model. 242-249 - Meiling Hao, Yunyuan Lin, Xingqiu Zhao:
A relative error-based approach for variable selection. 250-262 - Xuehu Zhu, Fei Chen, Xu Guo, Lixing Zhu:
Heteroscedasticity testing for regression models: A dimension reduction-based model adaptive approach. 263-283 - Wessel N. van Wieringen, Carel F. W. Peeters:
Ridge estimation of inverse covariance matrices from high-dimensional data. 284-303 - Zachary Zimmer, DoHwan Park, Thomas Mathew:
Tolerance limits under normal mixtures: Application to the evaluation of nuclear power plant safety and to the assessment of circular error probable. 304-315 - Heping He, Thomas A. Severini:
A flexible approach to inference in semiparametric regression models with correlated errors using Gaussian processes. 316-329 - Shibin Zhang:
Adaptive spectral estimation for nonstationary multivariate time series. 330-349 - Lynette A. Hunt, Kaye E. Basford:
Comparing classical criteria for selecting intra-class correlated features in Multimix. 350-366
- Alfredo Garbuno-Inigo, Francisco Alejandro DiazDelaO, Konstantin Zuev:
Gaussian process hyper-parameter estimation using Parallel Asymptotically Independent Markov Sampling. 367-383
- Lele Huang, Junlong Zhao, Huiwen Wang, Siyang Wang:
Robust shrinkage estimation and selection for functional multiple linear model through LAD loss. 384-400 - Sunghoon Kwon, Seungyoung Oh, Youngjo Lee:
The use of random-effect models for high-dimensional variable selection problems. 401-412 - Sijia Xiang, Weixin Yao, Byungtae Seo:
Semiparametric mixture: Continuous scale mixture approach. 413-425
- Lars Josef Höök, Erik Lindström:
Efficient computation of the quasi likelihood function for discretely observed diffusion processes. 426-437
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