Autoregressive Mixture Models for Dynamic Spatial Poisson Processes: Application to Tracking Intensity of Violent Crime
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Publication:5255683
DOI10.1198/jasa.2010.ap09655zbMath1388.62379OpenAlexW2090026919MaRDI QIDQ5255683
Publication date: 17 June 2015
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1198/jasa.2010.ap09655
Bayes factorssequential Monte Carlononparametricbeta processparticle learningdependent Dirichlet processtime-dependencestick-breakingmapping crime
Inference from spatial processes (62M30) Applications of statistics to social sciences (62P25) Bayesian inference (62F15) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)
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