rsfm_inla: Restricted Spatial Frailty Model in INLA

In DouglasMesquita/RASCO: An R Package to Alleviate Spatial Confounding

Restricted Spatial Frailty Model in INLA

Description

Fit a Restricted Spatial Frailty model using INLA

Usage

rsfm_inla(data, formula, family,
                 proj = "none", nsamp = 1000, fast = TRUE,
                 ...)

Arguments

data	a data frame or list containing the variables in the model.
formula	a inla formula like inla.surv(time, event) ~ 1 + z + f(ind, model="iid") + f(ind2, weights, model="ar1"). This is much like the formula for a glm except that smooth or spatial terms can be added to the right hand side of the formula. See f for full details and the web site www.r-inla.org for several worked out examples. Each smooth or spatial term specified through f should correspond to separate column of the data frame data. The outcome is the output of the function inla.surv.
family	"exponential", "weibull", "weibullcure", "loglogistic", "gamma", "lognormal" or "pwe".
proj	"none" or "rhz".
nsamp	number of samples. Default = 1000.
fast	set TRUE, to use the reduction operator.
...	other parameters used in ?INLA::inla.

Value

$unrestricted	A list containing $sample: a sample of size nsamp for all parameters in the model $summary_fixed: summary measures for the coefficients $summary_hyperpar: summary measures for hyperparameters $summary_random: summary measures for random quantities
$restricted	A list containing $sample: a sample of size nsamp for all parameters in the model $summary_fixed: summary measures for the coefficients $summary_hyperpar: summary measures for hyperparameters $summary_random: summary measures for random quantities
$out	INLA output
$time	time elapsed for fitting the model

DouglasMesquita/RASCO documentation built on Nov. 16, 2022, 9:42 p.m.