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General structure of the Gaussian Field Latent Class model.

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posted on 17.01.2013, 01:31 by Corentin M. Barbu, Andrew Hong, Jennifer M. Manne, Dylan S. Small, Javier E. Quintanilla Calderón, Karthik Sethuraman, Víctor Quispe-Machaca, Jenny Ancca-Juárez, Juan G. Cornejo del Carpio, Fernando S. Málaga Chavez, César Náquira, Michael Z. Levy

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.

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