Presented by Angélica Portocarrero and Xilena Atenea Rojas.
This repository contains the work for an academic project focused on analyzing the spatial distribution of homicides resulting from traffic accidents in Cali, Colombia, for the years 2009 and 2010. The analysis employs advanced spatial statistics techniques, including Kernel Density Estimation (KDE) and non-homogeneous Poisson models, to identify patterns and high-risk areas in the city. The goal is to provide a comprehensive understanding of how factors such as gender, age, and condition influence the occurrence of these incidents, with the hope that this study can serve as a valuable resource for those studying point patterns and related topics in spatial analysis.
This repository contains two main files:
Point_Patterns.pdf: This file includes the detailed report of the analysis, explaining the methodology, findings, and interpretations of the results. It covers the exploratory data analysis, point pattern analysis, and model fitting, providing a comprehensive guide to the entire process.
script_activity3: The R script used to perform the analysis. It includes the code for data cleaning, exploratory analysis, point pattern analysis using KDE and inhomogeneous K functions, and the implementation of non-homogeneous Poisson models.
This repository is designed to be a helpful resource for anyone interested in studying spatial point patterns, particularly in the context of traffic accidents. Whether you are a student, researcher, or practitioner, we hope that this repository provides valuable insights and practical examples to aid in your understanding and application of point pattern analysis.
Feel free to explore the files and use them as a reference for your own studies or projects.