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Computational Statistics & Data Analysis, Volume 114

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Volume 114, October 2017

Section I: Computational Statistics

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Justine Shults:
Simulating longer vectors of correlated binary random variables via multinomial sampling. 1-11
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Philip L. H. Yu, Xiaohang Wang, Yuanyuan Zhu:
High dimensional covariance matrix estimation by penalizing the matrix-logarithm transformed likelihood. 12-25
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  - journals/csda/CarzolioL17
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Marcos Carzolio, Scotland Leman:
Weighted particle tempering. 26-37
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  - journals/csda/GoryninDMP17
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Ivan Gorynin, Stéphane Derrode, Emmanuel Monfrini, Wojciech Pieczynski:
Fast smoothing in switching approximations of non-linear and non-Gaussian models. 38-46

Section II: Statistical Methodology for Data Analysis

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Shonosuke Sugasawa, Tatsuya Kubokawa:
Transforming response values in small area prediction. 47-60
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Jong-June Jeon, Sunghoon Kwon, Hosik Choi:
Homogeneity detection for the high-dimensional generalized linear model. 61-74
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Adrian J. Baddeley, Andrew Hardegen, Thomas Lawrence, Robin K. Milne, Gopalan M. Nair, Suman Rakshit:
On two-stage Monte Carlo tests of composite hypotheses. 75-87
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Xingxiang Li, Guosheng Cheng, Liming Wang, Peng Lai, Fengli Song:
Ultrahigh dimensional feature screening via projection. 88-104
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Chang Yu, Daniel Zelterman:
A parametric model to estimate the proportion from true null using a distribution for p-values. 105-118
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Shyamsundar Sahoo, Debasis Sengupta:
Testing the hypothesis of increasing hazard ratio in two samples. 119-129
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Matthieu Marbac, Mohammed Sedki:
A family of block-wise one-factor distributions for modeling high-dimensional binary data. 130-145
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Chunlin Wang, Paul Marriott, Pengfei Li:
Testing homogeneity for multiple nonnegative distributions with excess zero observations. 146-157

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