Statistical Models

Since our exploratory and clustering analysis highlighted evident correlations, we decided to quantify the relationship between service requests and neighborhood characteristics in the context of space, time or other confounding factors. In order to do this, we used Poisson Generalized Linear Models (GLM), a suitable formalism to model rates since- among its other useful properties- it accounts for the fact that service requests must be integer-valued and time independent.

A Poisson GLM relates a dependent variable, in our case the amount of service request per each type, with a set of independent factors (time, neighborhood characteristics) through an exponential relation. To put this in formal, mathematical terms, we denote as the volume of requests for a particular service in a given census tract, and consider the following model: