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Yu-Shan Shih

Yu-Shan Shih

office: Room 429

Phone: (05)2720411#66114

Fax: (05)2720497

Email: mthyss@ccu.edu.tw / albertyushan@gmail.com

Specialized Areas


  • Decision Tree Computing 
  • Multivariate Method

Degree Institution

  • Ph.D. in Statistics, University of Wisconsin-Madison



Journal Articles

  1. G. Rau and Y.-S. Shih (2021). Evaluation of Cohen’s kappa and other measures of inter-rater agreement for genre analysis and other nominal data. Journal of English for Academic Purposes, vol 53, 101026
  2. N.-T. Liu, F.-C. Lin and Y.-S. Shih (2020). Count regression trees. Advances in Data Analysis and Classification. vol 14, pp. 5-27.
  3. Y.-S. Shih and K.-H. Liu (2019). Regression trees for detecting preference patterns from rank data. Advances in Data Analysis and Classification. vol. 13, pp. 683-702.
  4. Liu, Kuang-Hsun; Shih, Yu-Shan. (2016) Score-scale decision tree for paired comparison data. Statist. Sinica 26, no. 1, 429–444. 
  5. Hsin-Ju Chang, Yu-Shan Shih* and Tsung-Jen Su (2014, Jun). Split selection methods for regression tree on detecting regional economic convergence. Journal of the Chinese Statistical Association, 52, 180-208. NSC 100-2118-M-194-001.
  6. Yi-Hung Kung, Chang-Ting Lin, Yu-Shan Shih* (2012, Sep). Split variable selection for tree modeling on rank data. Computational Statistics and Data Analysis, vol 56, pp. 2830-2836. (SCI). NSC 101-2118-M-194-001. 本人為通訊作者.
  7. Shu-Fu Kuo, Yu-Shan Shih* (2012, Jul). Variable selection for functional density trees. Journal of Applied Statistics, vol 39, pp. 1387-1395. (SCI). NSC 96-2118-M-194-001-MY2. 
  8. Li-Ling Chuang, Y.-S. Shih* (2012, Feb). Approximated distributions of the weighted sum of correlated chi-squared random variables. Journal of Statistical Planning and Inference, vol 142, pp. 457-472. (SCI). 
  9. H. Kim, W.-Y. Loh, Y.-S. Shih, and P. Chaudhuri (2007).  Visualizable and interpretable regression models with good prediction power. IIE Transactions, vol 39, 565-579. (SCI). NSC 92-2118-M-194-001.
  10. W.-C. Hsiao and Y.-S. Shih (2007). Splitting variable selection for multivariate regression trees. Statistics and Probability Letters, vol 77, 265-271. (SCI). NSC 94-2118-M-194-002.
  11. T.-H. Lee and Y.-S. Shih (2006). Unbiased variable selection for classification trees with multivariate responses. Computational Statistics and Data Analysis, vol 51, 659-667. (SCI). NSC 94-2118-M-194-002.
  12. Y.-S. Shih (2004, ). A Note on Split Selection Bias in Classification Trees. Computational Statistics and Data Analysis, vol 45, pp. 457-466. (SCI). NSC 90-2118-M-194-001.
  13. Y.-S. Shih* and H.-W. Tasi (2004). Variable selection bias in regression trees with constant fits. Computational Statistics and Data Analysis, vol. 45, pp. 595-607. (SCI). NSC 91-2118-M-194-001.
  14. D.-S. Liu*, Y.-S. Shih, C.-Y. Ni, D.-Y. Chiou, C.-L. Chung, and M.-L. Huang (2002, Nov). Influences of material source, wafer process and location on silicon die fracture strength. Experimental Techniques, vol. 26, pp. 29–35. (EI).
  15. Y.-S. Shih (2001). Selecting the best splits classification trees with categorical variables. Statistics and Probability Letters, vol. 54, pp. 341-345. (SCI).
  16. T.-S. Lim, W.-Y. Loh*, and Y.-S. Shih (2000). A comparison of prediction accuracy, complexity, and training time of thirty-three old and new classification algorithms. Machine Learning, vol. 40, pp. 203-228. (SCI). NSC 89-2118-M-194-005.
  17. Yu-Shan Shih (1999). Families of splitting criteria for classification trees. Statistics and Computing , 9, 309-315. (SCI). 
  18. Y.-S. Shih and W.-Y. Wu (1997). Studies on split selection methods for tree-structured regression. Journal of the Chinese Statistical Association, vol. 35, pp. 137-150.
  19. W.-Y. Loh and Y.-S. Shih (1997, Jul). Split selection methods for classification trees . Statistica Sinica, vol 7, 815-840. (SCI).


  1. Bolt, D. M., Dowling, N. M., Shih, Y.-S., and Loh, W.-Y.. Using Blinder-Oaxaca decomposition to explore differential item functioning: Application to PISA 2009 reading. Test fairness in the new generation of large-scale assessment (ISBN: 1681238934). Charlotte, NC 28271, USA: Information Age Publisher. Jun, 2017: 161-183. http://www.infoagepub.com/products/Test-Fairness-in-the-New-Generation-of-Large-Scale-Assessment.


  1. Wei-Yin Loh, Yu-Shan Shih (2015). QUEST Classification Tree.
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