Forthcoming Issue
The following papers are expected to appear in
Volume 27, Number 3, July 2017
General |
1. SS-2015-0364 |
doi:10.5705/ss.202015.0364 |
Parametric or nonparametric: The FIC approach
Martin Jullum and N.L. Hjort |
2. SS-2015-0473 |
doi:10.5705/ss.202015.0473 |
Variable selection via partial correlation
Jingyuan Liu, Runze Li and Lejia Lou |
3. SS-2015-0281 |
doi:10.5705/ss.202015.0281 |
Two-level minimum aberration designs under a conditional model with a pair of conditional and conditioned factors
Rahul Mukerjee, Jeff C.F. Wu and Ming-Chung Chang |
4. SS-2015-0355 |
doi:10.5705/ss.202015.0355 |
Risk consistency of cross-validation with Lasso-type procedures
Darren Homrighausen and Daniel J. McDonald |
5. SS-2015-0354 |
doi:10.5705/ss.202015.0354 |
An improved corrected score estimator for the proportional hazards model with time-dependent covariates measured with error at informative observation times
Xiao Song |
6. SS-2015-0347 |
doi:10.5705/ss.202015.0347 |
Semiparametric regression analysis of recurrent gap times in the presence of competing risks
Chia-Hui Huang, Yi-Hau Chen and Ya-Wen Chuang |
7. SS-2014-0153 |
doi:10.5705/ss.202014.0153 |
Semiparametric regression analysis of repeated current status data
Baosheng Liang, Xingwei Tong, Donglin Zeng and Yuanjia Wang |
8. SS-2015-0318 |
doi:10.5705/ss.202015.0318 |
Heteroscedastic nested error regression models with variance functions
Shonosuke Sugasawa and Tatsuya Kubokawa |
9. SS-2015-0382 |
doi:10.5705/ss.202015.0382 |
A Bayesian generalized CAR model for correlated signal detection
Andrew Brown, Gauri Datta and Nicole Lazar |
10. SS-2015-0463 |
doi:10.5705/ss.202015.0463 |
Pseudo-Kernel method in U-statistic variance estimation with large kernel size
Qing Wang and Bruce Lindsay |
11. SS-2014-0141 |
doi:10.5705/ss.202014.0141 |
A general approach to goodness of fit for U-processes
Youngjoo Cho and Debashis Ghosh |
12. SS-2015-0332 |
doi:10.5705/ss.202015.0332 |
Bias adjustment of the Chao estimator for the size of a population
Chang Xuan Mao, Sijia Zhang and Zhilin Liao |
13. SS-2015-0380 |
doi:10.5705/ss.202015.0380 |
Information criteria for prediction when distributions of data and target variables are different
Keisuke Yano and Fumiyasu Komaki |
14. SS-2015-0362 |
doi:10.5705/ss.202015.0362 |
Bayesian multiple testing under sparsity for polynomial-tailed distributions
Xueying Tang, Ke Li and Malay Ghosh |
15. SS-2015-0179 |
doi:10.5705/ss.202015.0179 |
Sparse and robust linear regression: an optimization algorithm and its statistical properties
Shota Katayama and Hironori Fujisaman |
16. SS-2016-0243 |
doi:10.5705/ss.202016.0243 |
Upper expectation parametric regression
Lixing Zhu, Lu Lin, Ping Dong and Yunquan Song |
17. SS-2015-0070 |
doi:10.5705/ss.202015.0070 |
Generalized partial linear models with unknown link and unknown baseline functions for longitudinal data
Huazhen Lin, Ling Zhou and Binhuan Wang |
18. SS-2015-0011 |
doi:10.5705/ss.202015.0011 |
The effect of L1 penalization on condition number constrained estimation of precision matrix
Chunming Zhang and Xiao Guo |
19. SS-2016-0116 |
doi:10.5705/ss.202016.0116 |
More powerful multiple testing in randomized experiments with non-compliance
Joseph J. Lee, Laura Forastiere, Luke Miratrix and Natesh S. Pillai |
20. SS-2015-0161 |
doi:10.5705/ss.202015.0161 |
Generators for nonregular 2k-p designs
Robert W Mee |
21. SS-2015-0385 |
doi:10.5705/ss.202015.0385 |
Optimal design for multiple regression with information driven by the linear predictor
Dennis Schmidt and Rainer Schwabe |
22. SS-2015-0219 |
doi:10.5705/ss.202015.0219 |
Simultaneous confidence bands in nonlinear regression models with nonstationarity
Degui Li, Weidong Liu, Qiying Wang and Weibiao Wu |
23. SS-2015-0426 |
doi:10.5705/ss.202015.0426 |
Bandwidth selection for estimating the two-point correlation function of a spatial point pattern using AMSE
Ji Meng Loh and Woncheol Jang |
24. SS-2015-0199 |
doi:10.5705/ss.202015.0199 |
Composite T2 test for high-dimensional data
Long Feng, Changliang Zou, Zhaojun Wang and Lixing Zhu |
25. SS-2015-0185 |
doi:10.5705/ss.202015.0185 |
Robust principal component analysis based on trimming around affine subspaces
Christophe Croux, Luis Angel García-Escudero, Alfonso Gordaliza, Christel Ruwet and Roberto San Martín |
26. SS-2015-0357 |
doi:10.5705/ss.202015.0357 |
When is acceleration unnecessary in a degradation test?
Zhisheng Ye and Lanqing Hong |