A function to define priors for the MCMC.
mcmcPriors(
betaprior = NULL,
omegaprior = NULL,
etaprior = NULL,
call = NULL,
derivative = NULL
)an object of class mcmcPriors
prior for beta, the covariate effects
prior for omega, the parameters of the baseline hazard
prior for eta, the parameters of the latent field
function to evaluate the log-prior e.g. logindepGaussianprior
function to evaluate the first and second derivatives of the prior
The package spatsurv only provides functionality for the built-in Gaussian priors. However, the choice of prior is
extensible by the user by creating functions similar to the functions betapriorGauss, omegapriorGauss, etapriorGauss,
indepGaussianprior and derivindepGaussianprior: the first three of which provide a mechanism for storing and retrieving the
parameters of the priors; the fourth, a function for evaluating the log of the prior for a given set of parameter values; and the fifth, a
function for evaluating the first and second derivatives of the log of the prior. It is assumed that parameters are a priori independent.
The user interested in using other priors is encouraged to look at the structure of the five functions mentioned above.
survspat, betapriorGauss, omegapriorGauss, etapriorGauss, indepGaussianprior, derivindepGaussianprior