A functional log-Gaussian Cox approach to predict disease mortality patterns in space and time

A. Torres Signes, M. P. Frías Bustamante, M. D. Ruiz-Medina

A new approach is presented for the statistical analysis of disease mortality patterns in space and time, based on log-Gaussian Cox processes in function spaces. Specifically, this approach involves two steps: (i) The functional parameter estimation of the spatial log-intensity, taking values in a separable Hilbert space; (ii) The functional plug-in prediction of the values of the underlying log-Gaussian Cox process on a time interval, at each spatial region of interest. The results derived are applied to spatial functional prediction of respiratory disease mortality over the Spanish provinces in the Iberian Peninsula.

Keywords: FDA tools, Functional Log-Gaussian Cox Processes, Mortality Patterns, Spatial Functional Statistics.

EET-1 ST-2 Spatial Statistics and Temporal Space. Time Series
September 4, 2019  2:45 PM
I2L5. Georgina Blanes building

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