Autoregressive Mixture Models for Dynamic Spatial Poisson Processes: Application to Tracking Intensity of Violent Crime

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Bayesian Nonparametric Calibration and Combination of Predictive Distributions (2015, methodology): “This type of prior, and its multivariate extensions (e.g., see Müller, Quintana, and Rosner 2004 and Griffin and Steel 2006), is now widely used in many fields due to the availability of efficient algorithms for posterior computations (Escobar and West 1995; MacEachern and Müller 1998; Papaspiliopou”
Bayesian Inference and Model Assessment for Spatial Point Patterns Using Posterior Predictive Samples (2017, methodology): “Finally, we find some quite recent Bayesian model checking work, primarily validating intensities, in Taddy (2010), Zhou et al. (2015), and Xiao et al. (2015).”
Mixture Modeling for Marked Poisson Processes (2010, background): “For instance, Taddy (2010) presents an estimation of weekly violent crime intensity surfaces, using autoregressive modeling for marked spatial NHPPs, and Kottas et al. (2011) compares neuronal firing intensities recorded under multiple experimental conditions, using hierarchically dependent…”