mcmcPriors: mcmcPriors function

In bentaylor1/spatsurv: Bayesian Spatial Survival Analysis with Parametric Proportional Hazards Models

Description

A function to define priors for the MCMC.

Usage

mcmcPriors(betaprior = NULL, omegaprior = NULL, etaprior = NULL,
  call = NULL, derivative = NULL)

Arguments

betaprior	prior for beta, the covariate effects
omegaprior	prior for omega, the parameters of the baseline hazard
etaprior	prior for eta, the parameters of the latent field
call	function to evaluate the log-prior e.g. logindepGaussianprior
derivative	function to evaluate the first and second derivatives of the prior

Details

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.

Value

an object of class mcmcPriors

See Also

survspat, betapriorGauss, omegapriorGauss, etapriorGauss, indepGaussianprior, derivindepGaussianprior

bentaylor1/spatsurv documentation built on May 12, 2019, 3:02 p.m.