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>.

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>).

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

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>.