Implementing a kriging algorithm for modeling spatial data is not difficult, unless you choose to code every step yourself. Once the data is prepared with correct spatial attributes, the legwork is done by software packages available in all major programming languages (here is an example with Baltimore crime data implemented in R). Sometimes it helps […]

In the previous post I analyzed a 12-yr long crime data from 2011 to 2022 in the city of Baltimore, and described the yearly trends and spatial patterns observed in the crime activity. Here I talk about how to model this data to predict crimes anywhere in the city. I chose year 2022 data to

Availability of high-quality data on the time and location of major crimes in the city of Baltimore makes studying the characteristics of such crimes a data scientist’s delight. I have used a 12-year long dataset spanning from Jan-2011 to Dec-2022 (updated from the time of posting) to explore trends and patterns of violent crimes within