Virgilio Gf3mez-Rubio

A set of functions for the detection of spatial clusters of disease using count data. Bootstrap is used to estimate sampling distributions of statistics.

Model-based methods for the detection of disease clusters using GLMs, GLMMs and zero-inflated models. These methods are described in 'V. G<c3><b3>mez-Rubio et al.' (2019) <doi:10.18637/jss.v090.i14> and 'V. G<c3><b3>mez-Rubio et al.' (2018) <doi:10.1007/978-3-030-01584-8_1>.

This package provides some functions to create quizzes in the GIFT format. This format is used by several Virtual Learning Environments such as Moodle.

Fit Spatial Econometrics models using Bayesian model averaging on models fitted with INLA. The INLA package can be obtained from <http://www.r-inla.org>.

Implementation of several multivariate areal latent effects for 'INLA' using the 'rgeneric' latent effect (Palm<c3><ad>-Perales et al., 2019, <arXiv:1909.10804>). The 'INLA' package can be downloaded from <http://www.r-inla.org>. In particular, the package includes latent effects ready to use for several multivariate spatial models: intrinsic CAR, proper CAR and the M-model (Botella-Rocamora et al., 2015, <doi:10.1002/sim.6423>).

Edge-corrected kernel density estimation and binary kernel regression estimation for multivariate spatial point process data. For details, see Diggle, P.J., Zheng, P. and Durr, P. A. (2005) <doi:10.1111/j.1467-9876.2005.05373.x>.