Research and Academic Interests
My main research interest lies in the development of sound data science methods that are directly usable by practitioners. I have been using fractional calculus-based methods to generalize and improve widely used techniques. The generality and the flexibility of these methodologies make them more attractive in practice than their classical counterparts. Additionally, I am interested in intensive computational or quantitative techniques (e.g., simulation, bootstrap) to deal with the seemingly analytically intractable aspects of data science. Another area that is equally interesting for me is the development of formal effect estimation, uncertainty quantification, and hypothesis testing procedures in high dimensional data space.
Overall, I am passionate about continually improving traditional/classical statistical methodologies using new or other tools (e.g., fractional calculus-based methods, machine learning, Bayesian, robust techniques for big data science), sharing state-of-the-art or new methodologies to my students that will help them succeed in life, and providing better solutions to existing real-world problems.
Cahoy D, Minkabo S. (2017). Inference for three-parameter M-Wright distributions with applications. Model Assist Stat Appl, 12(2), 115-125.
Cahoy D. (2015). Some skew-symmetric distributions which include the bimodal ones. Commun Stat Theory Methods, 44(3), 554-563.
Cahoy D, Polito F. (2014). Parameter estimation for fractional birth and fractional death processes. Stat Comput, 24(2), 211-222.
Cahoy D, Polito F. (2013). Renewal processes based on generalized Mittag-Leffler waiting times. Commun Nonlinear Sci Numer Simul, 18(3), 639-650.
Cahoy D. (2012). An estimation procedure for the Linnik distribution. Statist. Papers, 53(3), 617-628.
Cahoy D, Polito F. (2012). Simulation and estimation of the fractional Yule process. Methodol Comput Appl Probab, 14(2), 383-403.
Cahoy D, Polito F. (2012). On a fractional binomial process. J Stat Phys, 146(3), 646-662.
Cahoy D. (2012). Moment estimators for the two-parameter M-Wright distribution. Comput Stat, 27(3), 487-497.
Cahoy D, Uchaikin V, Woyczynski W. (2010). Parameter estimation for fractional Poisson processes. J Stat Plan Inference, 140(11), 3106-3120.
Cahoy D. (2010). A bootstrap test for equality of variances. Comput Stat Data Anal, 54(10), 2306-2316.
Cahoy D, Sibatov R, Uchaikin V. (2008). Fractional processes: From Poisson to branching. Int J Bifurcat Chaos, 18(9), 2717-2725.
Louisiana Board of Regents-Research Competitiveness Subprogram award, Statistical methods for fractional birth-death processes, 2011-2014, role: PI
Fellowship at Center for Secure Cyberspace, Louisiana Tech University, Summer 2012,
Travel award to attend a conference and present a poster entitled Exploratory data mining and data requirements to support ToxCast goals in EPA, Research Triangle Park, NC, role: Presenter, $1.5k
Teaching Assistantship to pursue PhD-Statistics at Case Western Reserve University, USA, 2003-2007.
Teaching Assistantship to pursue MSc-Statistics at University of Alberta, Canada, 2001-2003
Full Scholarship (with a monthly stipend, free tuition, free board, and lodging) from the Philippine Commission on Higher Education to pursue MSc-Applied Mathematical Sciences at University of Science and Technology of Southern Philippines, 1997-1998.