BayesSPsurv: Bayesian Spatial Split Population Survival Model

Parametric spatial split-population (SP) survival models for clustered event processes. The models account for structural and spatial heterogeneity among “at risk” and “immune” populations, and incorporate time-varying covariates. This package currently implements Weibull, Exponential and Log-logistic forms for the duration component. It also includes functions for a series of diagnostic tests and plots to easily visualize spatial autocorrelation, convergence, and spatial effects. Users can create their own spatial weights matrix based on their units and adjacencies of interest, making the use of these models flexible and broadly applicable to a variety of research areas. Joo et al. (2020) <https://github.com/Nicolas-Schmidt/BayesSPsurv/blob/master/man/figures/SPcure.pdf> describe the estimators included in this package.

Getting started

Package details

AuthorBrandon L. Bolte [aut], Nicolas Schmidt [aut, cre], Sergio Bejar [aut], Minnie M. Joo [aut], Nguyen K. Huynh [aut], Bumba Mukherjee [aut]
MaintainerNicolas Schmidt <nschmidt@cienciassociales.edu.uy>
LicenseMIT + file LICENSE
Version0.1.4
URL https://nicolas-schmidt.github.io/BayesSPsurv/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("BayesSPsurv")

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BayesSPsurv documentation built on Sept. 13, 2021, 9:09 a.m.