Description Usage Arguments Value References
A function to evaluate the log-posterior of a spatial parametric proportional hazards model. Not intended for general use.
1 2 | logPosterior_SPDE(surv, X, beta, omega, eta, gamma, priors, cov.model, u,
control, gradient = FALSE, hessian = FALSE)
|
surv |
an object of class Surv |
X |
the design matrix, containing covariate information |
beta |
parameter beta |
omega |
parameter omega |
eta |
parameter eta |
gamma |
parameter gamma |
priors |
the priors, an object of class 'mcmcPriors' |
cov.model |
the spatial covariance model |
u |
vector of interpoint distances |
control |
a list containg various control parameters for the MCMC and post-processing routines |
gradient |
logical whether to evaluate the gradient |
hessian |
logical whether to evaluate the Hessian |
evaluates the log-posterior and the gradient and hessian, if required.
Benjamin M. Taylor. Auxiliary Variable Markov Chain Monte Carlo for Spatial Survival and Geostatistical Models. Benjamin M. Taylor. Submitted. http://arxiv.org/abs/1501.01665
Finn Lindgren, Havard Rue, Johan Lindstrom. An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach. Journal of the Royal Statistical Society: Series B 73(4)
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