survspat: survspat function

In spatsurv: Bayesian Spatial Survival Analysis with Parametric Proportional Hazards Models

survspat function

Description

A function to run a Bayesian analysis on censored spatial survial data assuming a proportional hazards model using an adaptive Metropolis-adjusted Langevin algorithm.

Usage

survspat(
  formula,
  data,
  dist,
  cov.model,
  mcmc.control,
  priors,
  shape = NULL,
  ids = list(shpid = NULL, dataid = NULL),
  control = inference.control(gridded = FALSE),
  boundingbox = NULL
)

Arguments

formula	the model formula in a format compatible with the function flexsurvreg from the flexsurv package
data	a SpatialPointsDataFrame object containing the survival data as one of the columns OR for polygonal data a data.frame, in which case, the argument shape must also be supplied
dist	choice of distribution function for baseline hazard. Current options are: exponentialHaz, weibullHaz, gompertzHaz, makehamHaz, tpowHaz
cov.model	an object of class covmodel, see ?covmodel ?ExponentialCovFct or ?SpikedExponentialCovFct
mcmc.control	mcmc control parameters, see ?mcmcpars
priors	an object of class Priors, see ?mcmcPriors
shape	when data is a data.frame, this can be a SpatialPolygonsDataFrame, or a SpatialPointsDataFrame, used to model spatial variation at the small region level. The regions are the polygons, or they represent the (possibly weighted) centroids of the polygons.
ids	named list entry shpid character string giving name of variable in shape to be matched to variable dataid in data. dataid is the second entry of the named list.
control	additional control parameters, see ?inference.control
boundingbox	optional bounding box over which to construct computational grid, supplied as an object on which the function 'bbox' returns the bounding box

Value

an object inheriting class 'mcmcspatsurv' for which there exist methods for printing, summarising and making inference from.

References

1. Benjamin M. Taylor and Barry S. Rowlingson (2017). spatsurv: An R Package for Bayesian Inference with Spatial Survival Models. Journal of Statistical Software, 77(4), 1-32, doi:10.18637/jss.v077.i04.

See Also

tpowHaz, exponentialHaz, gompertzHaz, makehamHaz, weibullHaz, covmodel, ExponentialCovFct, SpikedExponentialCovFct, mcmcpars, mcmcPriors, inference.control

spatsurv documentation built on Oct. 19, 2023, 9:07 a.m.