[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
:: ::
Back to the articles list Back to browse issues page
Bayesian Approach for Modelling Spatial–Temporal Crime Data
Ali Mohammadian mosammam * , Jorge Mateu
Abstract:   (401 Views)

An important issue in many cities is related to crime events, and spatio–temporal Bayesian approach leads to identifying crime patterns and hotspots. In Bayesian analysis of spatio–temporal crime data, there is no closed form for posterior distribution because of its non-Gaussian distribution and existence of latent variables. In this case, we face different challenges such as high dimensional parameters, extensive simulation and time-consuming computation in applying MCMC methods. In this paper, we use INLA to analyze crime data in Colombia. The advantages of this method can be the estimation of criminal events at a specific time and location and exploring unusual patterns in places.

Keywords: Integrated Nested Laplace Approximation, Bayesian Statistics, Spatial-temporal Statistics.
Full-Text [PDF 4205 kb]   (171 Downloads)    
Type of Study: Research | Subject: Spatial Statistics
Received: 2022/03/3 | Accepted: 2023/03/1
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA


XML   Persian Abstract   Print



Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Back to the articles list Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences

Persian site map - English site map - Created in 0.05 seconds with 30 queries by YEKTAWEB 4509