Prof TONG, Tiejun 童鐵軍教授
Professor
Associate Head
PhD, University of California at Santa Barbara
MSc, University of Science and Technology of China
BSc, University of Science and Technology of China
FSC 1201
(852) 3411-7340
Google Scholar
Researcher ID
Scopus
ORCID

Current Research Interests

High-dimensional data analysis
Meta-analysis and medical statistics
Nonparametric regression models

 

 

Selected Publications

  1. Jiajin Wei, Enxuan Lin, Jiandong Shi, Ke Yang, Zongliang Hu, Xiantao Zeng and Tiejun Tong (2021). Meta-analysis with zero-event studies: a comparative study with application to COVID-19 data. Military Medical Research, 8: 41.
  2. Sanying Feng, Gaorong Li, Heng Peng and Tiejun Tong (2021). Varying coefficient panel data model with interactive fixed effects. Statistica Sinica, 31: 935-957.
  3. Jiandong Shi, Dehui Luo, Hong Weng, Xiantao Zeng, Lu Lin, Haitao Chu and Tiejun Tong (2020). Optimally estimating the sample standard deviation from the five-number summary. Research Synthesis Methods, 11: 641-654.
  4. Hong Zhang, Tiejun Tong, John Landers and Zheyang Wu (2020). TFisher: A powerful truncation and weighting procedure for combining p-values. Annals of Applied Statistics, 14: 178-201.
  5. Wenwu Wang, Ping Yu, Lu Lin and Tiejun Tong (2019). Robust estimation of derivatives using locally weighted least absolute deviation regression. Journal of Machine Learning Research, 20(60): 1−49.
  6. Zongliang Hu, Tiejun Tong and Marc G. Genton (2019). Diagonal likelihood ratio test for equality of mean vectors in high-dimensional data. Biometrics, 75: 256-267.
  7. Dehui Luo, Xiang Wan, Jiming Liu and Tiejun Tong (2018). Optimally estimating the sample mean from the sample size, median, mid-range and/or mid-quartile range. Statistical Methods in Medical Research, 27: 1785-1805.
  8. Wenlin Dai, Tiejun Tong and Lixing Zhu (2017). On the choice of difference sequence in a unified framework for variance estimation in nonparametric regression. Statistical Science, 32: 455-468.
  9. Wenlin Dai, Tiejun Tong and Marc G. Genton (2016). Optimal estimation of derivatives in nonparametric regression. Journal of Machine Learning Research, 17(164): 1-25.
  10. Yebin Cheng, Dexiang Gao and Tiejun Tong (2015). Bias and variance reduction in estimating the proportion of true null hypotheses. Biostatistics, 16: 189-204.
  11. Xiang Wan, Wenqian Wang, Jiming Liu and Tiejun Tong (2014). Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Medical Research Methodology, 14: 135.
  12. Tiejun Tong, Yanyuan Ma and Yuedong Wang (2013). Optimal variance estimation without estimating the mean function. Bernoulli, 19: 1839-1854.
  13. Tiejun Tong, Liang Chen and Hongyu Zhao (2012). Improved mean estimation and its application to diagonal discriminant analysis. Bioinformatics, 28: 531-537.
  14. Tiejun Tong and Yuedong Wang (2007). Optimal shrinkage estimation of variances with applications to microarray data analysis. Journal of the American Statistical Association, 102: 113-122.
  15. Tiejun Tong and Yuedong Wang (2005). Estimating residual variance in non-parametric regression using least squares. Biometrika, 92: 821-830.

 

 

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