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dblp: Computational Statistics & Data Analysis, Volume 129

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Computational Statistics & Data Analysis, Volume 129

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Volume 129, January 2019

Statistical Methodology for Data Analysis

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Lin Lin, Duncan K. H. Fong:
Bayesian multidimensional scaling procedure with variable selection. 1-13
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Kan Li, Sheng Luo:
Bayesian functional joint models for multivariate longitudinal and time-to-event data. 14-29
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  - journals/csda/DickhausS19
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Thorsten Dickhaus, Natalia Sirotko-Sibirskaya:
Simultaneous statistical inference in dynamic factor models: Chi-square approximation and model-based bootstrap. 30-46
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  - journals/csda/ManghiCP19
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Roberto F. Manghi, Francisco José de A. Cysneiros, Gilberto A. Paula:
Generalized additive partial linear models for analyzing correlated data. 47-60
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  - journals/csda/HinoveanuLV19
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Laurentiu C. Hinoveanu, Fabrizio Leisen, Cristiano Villa:
Bayesian loss-based approach to change point analysis. 61-78
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  - journals/csda/ZangFCNZ19
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Yong Zang, Wing Kam Fung, Sha Cao, Hon Keung Tony Ng, Chi Zhang:
Robust tests for gene-environment interaction in case-control and case-only designs. 79-92
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  - journals/csda/YuDHWZS19
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Dalei Yu, Chang Ding, Na He, Ruiwu Wang, Xiaohua Zhou, Lei Shi:
Robust estimation and confidence interval in meta-regression models. 93-118
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Hsiang-Ling Hsu, Yuan-chin Ivan Chang, Ray-Bing Chen:
Greedy active learning algorithm for logistic regression models. 119-134
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Haiqiang Ma, Ting Li, Hongtu Zhu, Zhongyi Zhu:
Quantile regression for functional partially linear model in ultra-high dimensions. 135-147

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