Athanasios Christou Micheas

Associate Professor of Statistics

Publications

Textbook

1. Theory of Stochastic Objects: Probability, Stochastic Processes and Inference. Micheas, A.C. (2018). Chapman & Hall/CRC Texts in Statistical Science Series. Textbook Resources

Refereed Journal Papers

2. Prior and posterior predictive p-values in the one-sided location parameter testing problem. A.C. Micheas and D.K. Dey (2003). Sankhya, Series A, Vol 65, 158-178. Pdf file.

3. On Measuring Loss Robustness Using Maximum a posteriori Estimate. A.C. Micheas and D.K. Dey (2004). Communications in Statistics-Theory and Methods, Vol. 33, issue #5, 1069-1085. Pdf file.

4. Assessing shape differences in populations of shapes using the complex Watson shape distribution. A.C. Micheas and D.K. Dey (2005). Journal of Applied Statistics, Vol. 32, No. 2, 105-116.

5. Modeling shape distributions and inferences for assessing differences in shapes. A.C. Micheas and D.K. Dey (2005). Journal of Multivariate Analysis, 92, 257-280. Pdf file.

6. Complex Elliptical Distributions with Application to Shape Analysis. A.C. Micheas, D.K. Dey and K. Mardia (2006). Journal of Statistical Planning and Inference, 136, 2961-2982. Pdf file.

7. Measuring Stochastic Dependence using phi-divergence. A. C. Micheas and Konstantinos Zografos (2006). Journal of Multivariate Analysis, 97, 765-784. Pdf file.

8. A unified approach to Prior and Loss Robustness. A. C. Micheas (2006). Communications in Statistics-Theory and Methods, 35, 309-323. Pdf file.

9. Reconciling Bayesian and frequentist evidence in the one-sided scale parameter testing problem. A .C. Micheas and D.K. Dey, (2007). Communications in Statistics-Theory and Methods. Volume 36, Issue 6, 1123-1138. Pdf file.

10. Cell Identification and Verification of QPF Ensembles Using Shape Analysis Techniques. Athanasios Christou Micheas, Neil I. Fox, Steven A. Lack and Christopher K. Wikle (2007). Journal of Hydrology. doi:10.1016/j.jhydrol.2007.05.036.

11. A Bayesian Hierarchical Non-Overlapping Random Disc Growth Model. A. C. Micheas and C. K. Wikle (2009). Journal of the American Statistical Association, 104(485): 274-283. doi:10.1198/jasa.2009.0124. Pdf file.

12. Bayesian Procrustes Analysis with applications to Hydrology. A.C. Micheas and Y. Peng (2010). Journal of Applied Statistics, 37, 41-55. Pdf file.

13. Random Set Modeling of Three-Dimensional Objects in a Hierarchical Bayesian Context. A.C. Micheas, C.K. Wikle and David R. Larsen (2012). Journal of Statistical Computation and Simulation, 84, 1, 107-123. Pdf file.

14. Hierarchical Bayesian Modeling of Marked Non-Homogeneous Poisson Processes with finite mixtures and inclusion of covariate information. Micheas, A.C. (2014). Journal of Applied Statistics, Volume 41, Issue 12, pages 2596-2615, DOI: 10.1080/02664763.2014.922167. Pdf file.

15. Modeling the growth of objects through a stochastic process of random sets. Rima Dey and A.C. Micheas (2014). Journal of Statistical Planning and Inference, Volumes 151-152, 17-36. DOI: 10.1016/j.jspi.2014.03.007 Pdf file.

16. A Spatio-Temporal Point Process Model for Ambulance Demand. Zhengyi Zhou, David S. Matteson, Dawn B. Woodard, Shane G. Henderson, Athanasios C. Micheas (2015). Journal of the American Statistical Association. Volume 110, Issue 509, pages 6-15, DOI: 10.1080/01621459.2014.941466. Pdf file.

17. On local divergences between two probability measures. G. Avlogiaris, A. Micheas and K. Zografos (2016). Metrika, 79, 3, 303-333, DOI: 10.1007/s00184-015-055. Pdf file

18. On testing local hypothesis via local divergence. G. Avlogiaris, A. Micheas and K. Zografos (2016). Statistical Methodology, 31, 20-42. http://dx.doi.org/10.1016/j.stamet.2016.01.003 Pdf file.

19. Applications of Bayesian Procrustes Shape Analysis to Ensemble Radar Reflectivity Nowcast Verification. Neil Fox, A.C. Micheas and Yuqiang Peng (2016). Atmospheric Research, 176-177, 75-86. Pdf file.

20. Modeling the Evolution of a Random Set Utilizing Covariate Information with Applications to Nowcasting (2016). A.C. Micheas, Neil Fox, and Rima Dey. Journal of Statistical Computation and Simulation. DOI: 10.1080/00949655.2016.1182531. Pdf file.

21. A criterion for local model selection (2018). G. Avlogiaris, A.C. Micheas and K. Zografos. Sankhya A, 81(2), 406-444. Pdf file.

22. Spectrum Sensing Based on Bayesian Generalized Likelihood Ratio for Cognitive Radio Systems with Multiple Antennas (2018). M. Al-Amidie, A. Al-Asadi, A. C. Micheas, and N. E. Islam. IET Communications 13(3), 305-311.

23. sppmix: Poisson Point Process Modeling using Normal Mixture Models (2018). A. C. Micheas and J. Chen. Computational Statistics, 33, 4, 1767-1798. Pdf file.

24. Worst Case Fair Beamforming for Multiple Multicast Groups in Multicell Networks (2018). A. Al-Asadi, M. Al-Amidie, A. C. Micheas, R.C. Mc Garvey, and N. E. Islam. IET Communications, 13(6), 664-671.

25. Cox Point Processes: Why a Sample Size of One is Not Enough (2019). A.C. Micheas. International Statistical Review, 87 (2), 306-325. Pdf file.

26. Bayesian Modeling and Decision Theory for Non-Homogeneous Poisson Point Processes (2020). Chen, J., Micheas, A.C., and Holan, S.H. Spatial Statistics, 36, 100412 Pdf file.

27. A Comparative Study of Approximate Bayesian Computation Methods for Gibbs Point Processes (2020). Chen, J., Micheas, A. C., and Holan, S.H. Journal of Statistics and Applications. Special Issue in Honor of Bimal and Bikas Sinha. 18, 223248.

28. Modeling Fourier Expansions using Point Processes on the Complex Plane with Applications (2022). Weichao Wu  and Athanasios C. Micheas. Communications in Statistics - Simulation and Computation, 53 (5): 2207-2224.

29. Hierarchical Bayesian modeling of spatio-temporal area-interaction processes (2022). Jiaxun Chen, Athanasios C.Micheas, Scott H. Holan. Computational Statistics & Data Analysis, 167, 107349.

30. A New Construction of Covariance Functions for Gaussian Random Fields (2024). Weichao Wu  and Athanasios C. Micheas. Sankhya A, 86 (1), 530-574.

31. Random Mixture Cox Point Processes (2024). Athanasios C. Micheas. Annals of the Institute of Statistical Mathematics (to appear).

Refereed Book Chapters

32. Ranges of posterior expected losses and epsilon-robust actions. D.K. Dey and A.C. Micheas (2000). In: Robust Bayesian Analysis (Eds. D. Rios Insua and F.Ruggeri; Springer-Verlag). Lecture Notes Monograph Series, Series #152, 145-160. Pdf file.

33. Shape Classification procedures with Application to Schizophrenia Diagnosis (2007). Dipak K. Dey, Rosalee E. Zackula and Athanasios C. Micheas. In: Bayesian Statistics and Its Applications, edited by S.K. Upadhyay, U.Singh and D.K. Dey. Anamaya Publishers, New Delhi, India.

Refereed Book Reviews

34. Review of "Stationary Stochastic Processes: Theory and Applications" by Georg Lindgren, Journal of the American Statistical Association, pg 870.

35. Review of "Constrained Statistical Inference: Inequality, Order, and Shape Restrictions" by Silvapulle, M.J., and Sen, P.K., Journal of the American Statistical Association, 101, 391-392.

Proceedings Papers

36. Shape Classification procedures with applications. A.C. Micheas and D.K. Dey (2003). Proceedings of the Section on Bayesian Statistical Science, American Statistical Association, San Francisco, 2003

37. Cell identification and verification of QPF ensembles using shape analysis techniques. Micheas, A.C., Lack, S.A., Fox, N.I., and Wikle, C.K. (2006). 2nd International Symposium on Quantitative Precipitation Forecasting and Hydrology, Boulder, CO.

38. An evaluation of a Procrustes shape analysis verification tool using idealized cases. Lack, S.A., N.I. Fox and A. Micheas (2007). Preprints American Meteorological Society 22nd Conference on Weather Analysis and Forecasting/18th Conference on Numerical Weather Prediction, Park City, UT.

39. Dey, D.K., Zackula, R.E. and Micheas, A.C. (2006). Shape classification procedures with application to schizophrenia diagnosis. Bayesian Statistics and its Application. Proceedings of the International conference on Bayesian Statistics, Varanasi, India.

40. Hierarchical Bayesian Random Sets with Applications to Growth Models. A.C. Micheas (2011). Proceedings of the Section on Bayesian Statistical Science, American Statistical Association, Miami Beach FL, 2011 Pdf file

Technical Reports

41. On the Poisson Forest Problem. R.Vitale and A.C. Micheas (University of Connecticut-Storrs, Dept of Statistics, 2004)

42. Time series analysis of shapes using the complex Normal distribution. A.C. Micheas and Joe Cavanaugh (University of Missouri-Columbia, Dept of Statistics, 2004)