spBayesSurv

Bayesian Modeling and Analysis of Spatially Correlated Survival Data

Provides several Bayesian survival models for spatial/non-spatial survival data: proportional hazards (PH), accelerated failure time (AFT), proportional odds (PO), and accelerated hazards (AH), a super model that includes PH, AFT, PO and AH as special cases, Bayesian nonparametric nonproportional hazards (LDDPM), generalized accelerated failure time (GAFT), and spatially smoothed density estimation. The spatial dependence is modeled via frailties under PH, AFT, PO, AH and GAFT, and via copulas under LDDPM and PH. Model choice is carried out via LPML and DIC.

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Description file content

Package
spBayesSurv
Type
Package
Title
Bayesian Modeling and Analysis of Spatially Correlated Survival Data
Version
1.1.2
Date
2018-1-10
Author
Haiming Zhou and Timothy Hanson
Maintainer
Haiming Zhou
Description
Provides several Bayesian survival models for spatial/non-spatial survival data: proportional hazards (PH), accelerated failure time (AFT), proportional odds (PO), and accelerated hazards (AH), a super model that includes PH, AFT, PO and AH as special cases, Bayesian nonparametric nonproportional hazards (LDDPM), generalized accelerated failure time (GAFT), and spatially smoothed density estimation. The spatial dependence is modeled via frailties under PH, AFT, PO, AH and GAFT, and via copulas under LDDPM and PH. Model choice is carried out via LPML and DIC.
License
GPL (>= 2)
VignetteBuilder
knitr
Suggests
knitr
Depends
R (>= 3.0.2)
Imports
Rcpp (>= 0.11.1), survival, coda, methods, MASS, fields
LinkingTo
Rcpp, RcppArmadillo (>= 0.4.300.0)
NeedsCompilation
yes
Packaged
2018-01-11 03:32:59 UTC; Haiming
Repository
CRAN
Date/Publication
2018-01-11 12:36:14 UTC

install.packages('spBayesSurv')

1.1.2

5 days ago

Haiming Zhou

GPL (>= 2)

Depends on

R (>= 3.0.2)

Imports

Rcpp (>= 0.11.1), survival, coda, methods, MASS, fields

Suggests

knitr

Discussions