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.
MCMCpack, FastGP, stats, Rcpp (>= 1.0.3), coda, dplyr,
reshape2, ggplot2, ape

MCMCpack, FastGP, stats, Rcpp (>= 1.0.3), coda, dplyr,
reshape2, ggplot2, ape, progress

c(person(given = "Brandon L.",
family = "Bolte",
role = c("aut")),
person(given = "Nicolas",
family = "Schmidt",
role = c("aut", "cre"),
email = "nschmidt@cienciassociales.edu.uy"),
person(given = "Sergio",
family = "Bejar",
role = c("aut")),
person(given = "Minnie M.",
family = "Joo",
role = c("aut")),
person(given = "Nguyen K.",
family = "Huynh",
role = c("aut")),
person(given = "Bumba",
family = "Mukherjee",
role = c("aut")))
MCMCpack, FastGP, stats, Rcpp (>= 1.0.3), coda, dplyr,
reshape2, ggplot2, ape, progress, rworldmap, countrycode
Brandon L. Bolte [aut],
Nicolas Schmidt [aut, cre],
Sergio Bejar [aut],
Minnie M. Joo [aut],
Nguyen K. Huynh [aut],
Bumba Mukherjee [aut]

c(person("Marco", "Banterle", email = "marco.banterle@gmail.com", role = c("aut")),
person("Zhi", "Zhao", email = "zhi.zhao@medisin.uio.no", role = c("aut", "cre")),
person("Leonardo", "Bottolo", email = "lb664@cam.ac.uk", role = c("ctb")),
person("Sylvia", "Richardson", email = "sylvia.richardson@mrc-bsu.cam.ac.uk", role = c("ctb")),
person("Alex", "Lewin", email = "alex.lewin@lshtm.ac.uk", role = c("aut")),
person("Manuela", "Zucknick", email = "manuela.zucknick@medisin.uio.no", role = c("ctb")))
Bayesian seemingly unrelated regression with general variable selection and dense/sparse covariance matrix. The sparse seemingly unrelated regression is described in Banterle et al. (2018) <doi:10.1101/467019>.
The C++ files pugixml.cpp, pugixml.hpp and pugiconfig.hpp
are Copyright (C) 2006-2018 by Arseny Kapoulkine
(arseny.kapoulkine@gmail.com) and Copyright (C) 2003 by Kristen
Wegner (kristen@tima.net).
Rcpp, utils, xml2, stats, igraph, Matrix, fields, tikzDevice,
grDevices, graphics, BDgraph, data.table, plyr, scrime, gRbase
Marco Banterle [aut],
Zhi Zhao [aut, cre],
Leonardo Bottolo [ctb],
Sylvia Richardson [ctb],
Alex Lewin [aut],
Manuela Zucknick [ctb]