*Submitted papers*

1. Akinlawon, O.*, Karunamuni, R., Li, P., and Zhao, S. (2016). Controlling IER and EER in replicated regular two-level factorial experiments.

2. Liu*, Li, Liu and Pu, X. (2016) Hypothesis testing for quantitative trait locus effects in both mean and variance in genetic backcross studies.

3. Wang, C*., Marriott, P. and Li, P. (2016) Testing homogeneity for multiple nonnegative distributions with excess zero observations.

4. Li, S., Chen, J. and Li, P. (2016) MixtureInf: An R package for the inference of finite mixture models.

5. Liu, G.*, Li, P., Liu, Y. and Pu, X. (2016) On consistency of the MLE under finite mixture of location-scale distributions with a structural parameter.

6. Liu, Y., Li, P. and Qin, J. (2016) Maximum empirical likelihood estimation for abundance in a closed population from capture-recapture data.

R Code and example data are available here.

In press

In press

44. Liu, G.*, Fu, Y., Li, P. and Pu, X. (2016). Using differential variability to increase the power of the homogeneity test in a two-sample problem. Statistica Sinica. In Press.

43. Yu, T., Li, P. and Qin, J. (2016). Maximum smoothed likelihood density estimation in the two-sample problem with likelihood ratio ordering. Biometrika. In press.

42. Li, P., Liu, Y. and Qin, J. (2016). Semiparametric inference in a genetic mixture model. Journal of the American Statistical Association. In press.

41. Li, P. and Tian, Z.* (2016). Maximum smoothed likelihood estimation of the centre of a symmetric distribution. In Press.

2016

2016

40. Chen, B., Li, P., Qin, J. and Yu, T. (2016) Using a monotonic density ratio model to find the asymptotically optimal combination of multiple diagnostic tests. Journal of the American Statistical Association, 514, 861-874.

39. Niu, X.*, Li, P. and Zhang, P. (2016). Testing homogeneity in a scale mixture of normal distributions. Statistical papers, 57, 499-516.

R code is available here.

38. Zhao S. and Li P. (2016). Construction of minimum aberration blocked two-level regular factorial designs. Communications in Statistics -Theory and Methods, 45, 5028-5036.

37. Chen, J., Li, P. and Liu, Y. (2016). Sample-size calculation for tests of

homogeneity. The Canadian Journal of Statistics, 44, 82-101.

36. Chen, J. and Li, P. (2016). Testing the order of a normal mixture in mean. Communications in Mathematics and Statistics, 4, 21-38.

35. Zhao, S., Lin, K. J. D., and Li, P. (2016). A note on the construction of blocked two-level designs with general minimum lower order confounding. Journal of Statistical Planning and Inference, 172, 16-22.

*34. Qin, J., Zhang, H., Li, P., Albanes, D. and Yu, K. (2015). Use covariate specific disease prevalence information to increase the power of case-control study. Biometrika, 102,169-180.*

2015

2015

33. Zhang, P., Luo, D., Li, P., Sharpsten, L., and Medeiros, F. (2015). Log-gamma linear mixed-effects models for multiple outcomes with application to a longitudinal glaucoma study. Biometrical Journal, 57, 766-776.

2014

2014

32. Wiens, D. and Li, P. (2014). V-optimal designs for heteroscedastic Regression. Journal of Statistical Planning and Inference, 145, 125-138.

31. Serban, N. and Li, P. (2014). A statistical test for mixture detection with application to component identification in multi-dimensional biomolecular NMR studies. The Canadian Journal of Statistics, 42, 36-60.

30. Fu Y., Li P. and Chung S.* (2014) Sample size calculation for the modified likelihood ratio test in genetic linkage analysis. J Biomet Biostat 5:205. doi: 10.4172/2155-6180.1000205.

2013

29. Yu, T. and Li, P. (2013). Spatial shrinkage estimation of diffusion tensors on diffusion weighted imaging data. Journal of the American Statistical Association, 108, 864-875.

28. Zhao, S., Li, P. and Rohana Karunamuni (2013). Blocked two-level regular factorial designs with weak minimum aberration. Biometrika, 100,

249-253.

27. Zhao, S., Li, P., Zhang, R. and Karunamuni, R. (2013). Construction of blocked two-level regular designs with general minimum lower order confounding. Journal of Statistical Planning and Inference, 143, 1082-1090.

26. Zhao, S., Li, P. and Liu, M. (2013). Results on blocked resolution IV designs containing clear two-factor interactions. Journal of Complexity, 29, 389-395.

25. Manafiazar, G., McFadden T., Goonewardene L., Okine E., Basarab J., Li P. and Wang Z. (2013). Prediction of residual feed intake for first lactation dairy cows using orthogonal polynomial random regression. Journal of Dairy Science, 96, 7991-8001.

2012

24. Chen, J., Li, P. and Fu, Y. (2012). Inference on the order of a normal mixture. Journal of the American Statistical Association, 107, 1096-1105.

23. Wiens, D. and Li, P. (2012) A robust treatment of a dose-response study. Applied Stochastic Models in Business and Industry, 28, 164-173.

22. Liu, Y., Li, P. and Fu, Y. (2012) Testing homogeneity in a semi-parametric two-sample model. Journal of Probability and Statistics, vol. 2012, Article ID 537474, 15 pages, 2012. doi:10.1155/2012/537474.

2011

21. Li, P. and Qin, J. (2011). A new nuisance parameter elimination method with application to unordered homologous chromosome pairs problem. Journal of the American Statistical Association, 106, 1476-1484.

20. Chen, J and Li, P. (2011). Tuning EM-test for finite mixture models. The Canadian Journal of Statistics, 39, 389-404.

19. Li, P., Zhao, S. and Zhang, R. (2011). A theory on constructing 2n-m designs with general minimum lower order confounding. Statistica Sinica, 21,1571-1589.

18. Niu, X*, Li, P. and Zhang, P. (2011). Testing homogeneity in a multivariate mixture model. The Canadian Journal of Statistics, 39, 218-238.

17. Li, P. and Wiens, D. (2011). Robustness of design in dose-response studies, Journal of the Royal Statistical Society: Series B, 73, 215-238.

16. Chen, J. and Li, P. (2011). The limiting distribution of the EM-test of the order of a finite mixture. In Mixture Estimation and Applications, K. Mengersen, C. Robert, and D. M. Titterington (Eds.). Hoboken, New Jersey: Wiley. 55-75.

2010

15. Li, P. and Chen, J. (2010). Testing the order of a finite mixture model. Journal of the American Statistical Association, 105, 1084-1092.

2009

14. Chen, J. and Li, P. (2009). Hypothesis test for normal mixture models: the EM approach. The Annals of Statistics, 37, 2523-2542.

13. Li, P., Chen, J. and Marriott, P. (2009). Non-finite Fisher information and homogeneity: the EM approach. Biometrika, 96, 411-42.

12. Li, P. and Wang, D. (2009). Numerical analysis of the validity of uniform design in stated choice modeling. Transport Reviews, 29, 619-634.

2008

11. Chen, J., Li, P. and Fu, Y. (2008). Testing homogeneity in a mixture of von Mises distributions with a structural parameter. The Canadian Journal of Statistics, 36, 129-142.

10. Fu, Y., Chen, J. and Li, P. (2008). Modified likelihood ratio test for homogeneity in a mixture of von Mises distributions. Journal of Statistical Planning and Inference, 138, 667-681.

2007

9. Li, P., Liu, M. and Zhang, R. (2007). 2m41 designs with minimum aberration or weak minimum aberration. Statistical Paper, 48, 235-248.

8. Chen, J., Li, P. and Tan, X. (2007) Inference for von Mises mixture in mean directions and concentration parameters. Journal of Systems Science and Mathematical Science, 27, 59-67.

2006

7. Yang, J., Li, P., Liu, M. and Zhang, R. (2006). 2(n1+n2)-(k1+k2) fractional factorial split-plot designs containing clear effects. Journal of Statistical Planning and Inference, 136, 4450-4458.

6. Chen, B., Li, P., Liu, M. and Zhang, R. (2006). Some results on blocked regular 2-level fractional factorial designs with clear effects. Journal of Statistical Planning and Inference, 136, 4436-4449.

5. Li, P., Chen, B., Liu, M. and Zhang, R. (2006). A note on minimum aberration and clear criteria. Statistics and Probability Letters, 76, 1007-1011.

2005

4. Wang, D. and Li, P. (2005). Does uniform design really work in stated choice modeling? A simulation study. Transportmetrica, 1, 209-222.

3. Ai, M., Li, P. and Zhang, R. (2005). Optimal criteria and equivalence for nonregular fractional factorial designs. Metrika, 62, 73-83.

2. Li, P., Liu, M. and Zhang, R. (2005). Choice of optimal initial designs in sequential experiments. Metrika, 61, 127-135.

2004

1. Li, P., Liu, M. and Zhang, R. (2004). Some theory and the construction of mixed-level supersaturated designs. Statistics and Probability Letters, 69, 105-116.