R Karunamuni, PhD

Email

rkarunam@ualberta.ca

Research Interests

My current research interests include efficient robust inference for parametric and semiparametric models, variable selection and high-dimensional data problems. 

Selected Publications

1. Q. Tang and R.J. Karunamuni (2016). Fast and accurate computation of kernel estimators. Computational Statistics and Data Analysis, 94, 49-62.

2. R.J. Karunamuni, Q. Tang and B. Zhao (2015). Robust and efficient estimation of effective dose. Computational Statistics and Data Analysis, 90, 47-60.

3. J. Wu and R.J. Karunamuni (2015). Profile Hellinger distance estimation. Statistics, 49, 711-740. 

4. Q. Tang and R.J. Karunamuni (2013). Minimum Hellinger distance estimation in a finite mixture regression model. Journal of Multivariate Analysis, 120, 185-204.

5. S. Zhao, P. Li and R. Karunamuni (2013). Blocked two-level regular factorial designs with weak minimum aberration. Biometrika, 100, 249-253.

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

7. J. Wu and R.J. Karunamuni (2012). Efficient Hellinger distance estimates for semiparametric models. Journal of Multivariate Analysis, 107, 1-23.

8. R.J. Karunamuni and J. Wu (2011). One-step minimum Hellinger distance estimation. Computational Statistics and Data Analysis, 55, 3148-3164.

9. J. Kolacek and R.J. Karunamuni (2011). A generalized reflection method for kernel distribution and hazard function estimation. Journal of Applied Probability and Statistics, 6, 73-85.

10. J. Wu, R.J. Karunamuni and B. Zhang (2010). Minimum Hellinger distance estimation in a two-sample semiparametric model. Journal of Multivariate Analysis, 101, 1102-1122.

11. R.J. Karunamuni, J. Li and J. Wu (2010). Robust empirical Bayes tests for continuous distributions. Journal of Statistical Planning and Inference, 140, 268-282.

12. S. Zhang and R.J. Karunamuni (2010). Boundary performance of the beta-kernel estimator. Journal of Nonparametric Statistics, 22, 81-104.

13. J. Wu and R.J. Karunamuni (2009). On minimum Hellinger distance estimation. The Canadian Journal of Statistics, 37, 514-533.

14. R.J. Karunamuni and J. Wu (2009). Minimum Hellinger distance estimation in a nonparametric mixture model. Journal of Statistical Planning and Inference, 139, 1118-1133. 

15. S. Zhang and R.J. Karunamuni (2009). Deconvolution boundary kernel method in nonparametric density estimation. Journal of Statistical Planning and Inference, 139, 2269-2283. 

For rest of the articles see: https://www.dropbox.com/s/txa59j43k42umr0/Research%20Papers%20of%20R.J.%20Karunamuni.pdf