Figure 1. General structure of the Gaussian Field Latent Class model.

Working backward, we consider the infestation data to be the result of a latent infestation status , observed by imperfect inspectors of sensitivity . The true infestation is a binary manifestation of an underlying continuous infestation predictor . Cofactors and a local error term, , form the local component. The spatial component is modeled as a Gaussian field. The fit parameters, and , respectively tune how distances between neighbors and the streets define the spatial dependency between households in the spatial component.