proposalVariance_SPDE

A function to compute an approximate scaling matrix for the MCMC algorithm. Not intended for general use.

Bayesian inference for parametric proportional hazards spatial
survival models; flexible spatial survival models. See Benjamin M. Taylor, Barry S. Rowlingson (2017) <doi:10.18637/jss.v077.i04>.

Benjamin Taylor

spatsurv

Bayesian Spatial Survival Analysis with Parametric Proportional
Hazards Models

proposalVariance_SPDE function

<dl><dt>X</dt>
<dd>the design matrix, containing covariate information</dd>
<dt>surv</dt>
<dd>an object of class Surv</dd>
<dt>betahat</dt>
<dd>an estimate of beta</dd>
<dt>omegahat</dt>
<dd>an estimate of omega</dd>
<dt>Yhat</dt>
<dd>an estimate of Y</dd>
<dt>priors</dt>
<dd>the priors</dd>
<dt>cov.model</dt>
<dd>the spatial covariance model</dd>
<dt>u</dt>
<dd>a vector of pairwise distances</dd>
<dt>control</dt>
<dd>a list containg various control parameters for the MCMC and post-processing routines</dd></dl>

Arguments

proposalVariance_SPDE function — proposalVariance_SPDE

<dl>

<dt>X</dt>
<dd>the design matrix, containing covariate information</dd>


<dt>surv</dt>
<dd>an object of class Surv</dd>


<dt>betahat</dt>
<dd>an estimate of beta</dd>


<dt>omegahat</dt>
<dd>an estimate of omega</dd>


<dt>Yhat</dt>
<dd>an estimate of Y</dd>


<dt>priors</dt>
<dd>the priors</dd>


<dt>cov.model</dt>
<dd>the spatial covariance model</dd>


<dt>u</dt>
<dd>a vector of pairwise distances</dd>


<dt>control</dt>
<dd>a list containg various control parameters for the MCMC and post-processing routines</dd>

</dl>

proposalVariance_SPDE: proposalVariance_SPDE function

Description

Usage

Value

Arguments