1. Rotational grid, PAI-maximizing crime forecasts. Statistical Analysis and Data Mining, : Accepted. (Mohler G. and Porter M.D.) [PDF]
2. Learning to rank spatio-temporal event hotspots. URBCOMP2018, 2018. (Mohler G., Porter M.D., Carter J., and LaFree G.) [PDF]
3. Optimal Bayesian Clustering using Non-negative Matrix Factorization. Computational Statistics and Data Analysis, 128: 395–411, 2018. (Wang K. and Porter M.D.) [PDF]
4. Consistency and specificity in burglars who commit prolific residential burglary: Testing the core assumptions underpinning behavioural crime linkage. Legal and Criminological Psychology, 21(1): 77–94, 2016. (Bouhana N., Johnson S.D., and Porter M.D.) [PDF]
5. A Statistical Approach to Crime Linkage. The American Statistician, 70(2): 152–165, 2016. (Porter M.D.) [PDF]
6. How the Choice of Safety Performance Function Affects the Identification of Important Crash Prediction Variables. Accident Analysis & Prevention, 88(1): 1–8, 2016. (Wang K., Simandl J.K., Porter M.D., Graettinger A.J., and Smith R.K.) [PDF]
7. Partially-supervised spatiotemporal clustering for burglary crime series identification. Journal of the Royal Statistical Society: Series A (Statistics in Society), 178(2): 465–780, 2015. (Reich B.J. and Porter M.D.) [PDF]
8. GPU accelerated MCMC for modeling terrorist activity. Computational Statistics & Data Analysis, 71: 643–651, 2014. (White G. and Porter M.D.) [PDF]
9. Modelling the effectiveness of counter-terrorism interventions. Trends & Issues in Crime and Criminal Justice, (457): 1–8, 2014. (White G., Mazerolle L., Porter M.D., and Chalk P.) [PDF]
10. Discussion of "Estimating the historical and future probabilities of large terrorist events'’. The Annals of Applied Statistics, 7(4): 1871–1875, 2013. (Reich B.J. and Porter M.D.) [PDF]
11. Terrorism Risk, Resilience, and Volatility: A Comparison of Terrorism in Three Southeast Asian Countries. Journal of Quantitative Criminology, 29(2): 295–320, 2013. (White G., Porter M.D., and Mazerolle L.) [PDF]
12. Evaluating temporally weighted kernel density methods for predicting the next event location in a series. Annals of GIS, 18(3): 225–240, 2012. (Porter M.D. and Reich B.J.) [PDF]
13. Self-exciting hurdle models for terrorist activity. The Annals of Applied Statistics, 6(1): 106–124, 2012. (Porter M.D. and White G.) [PDF]
14. Innovative Methods for Terrorism and Counterterrorism Data. In Evidence-Based Counterterrorism Policy, Springer New York, 91–112, 2012. (Porter M.D., White G., and Mazerolle L.) [PDF]
15. Network Neighborhood Analysis. IEEE Int. Conf. on Intelligence and Security Informatics (ISI), 31-36, 2010. (Porter M.D. and Smith R.) [PDF]
16. Mixture Likelihood Ratio Scan Statistic for Disease Surveillance. Advances in Disease Surveillance, 5: 1, 2008. (Neimi J.B., Porter M.D., and Reich B.J.) [PDF]
17. Detecting local regions of change in high-dimensional criminal or terrorist point processes. Computational Statistics & Data Analysis, 51(5): 2753 – 2768, 2007. (Porter M.D. and Brown D.E.) [PDF]

In Progress

18. Endogenous and Exogenous Effects in Contagion and Diffusion Models of Terrorist Activity. (White G., Ruggeri F., and Porter M.D.) [PDF]
19. A Fast Two Stage Anomaly Detection Method for Large Dynamic Networks. (Li H. and Porter M.D.)
20. The Predictability of Highway Crash Hotspots. (Liao Y. and Porter M.D.)
21. Predictive Based Model Selection for Detecting Insider Cyber Security Threats. (Posey C., Porter M.D., Lowry P., and Moody G.)
22. Contagion and Diffusion Models for the Dynamics of Terrorist Activity. [Under Contract with CRC Press] (White G.W. and Porter M.D.)