extract_property

an <code>inla</code> result object

result

character; "mean", "sd", "mode", or some other column
identifier for inla result <code>$summary.fixed</code>, <code>$summary.random$label</code>, and
<code>$summary.hyperpar</code>, or "joint_mode". For "joint_mode", the joint latent mode
is extracted, and the joint hyperparameter mode, in the internal scale.

property

logical; if <code>TRUE</code>, use internal scale for
hyperparamter properties. Default is <code>FALSE</code>, except when <code>property</code> is
"joint_mode" which forces <code>internal_hyperpar=TRUE</code>.

internal_hyperpar

Extract a summary property from all results of an inla result

internal

Facilitates spatial and general latent Gaussian modeling using
integrated nested Laplace approximation via the INLA package (<https://www.r-inla.org>).
Additionally, extends the GAM-like model class to more general nonlinear predictor
expressions, and implements a log Gaussian Cox process likelihood for
modeling univariate and spatial point processes based on ecological survey data.
Model components are specified with general inputs and mapping methods to the
latent variables, and the predictors are specified via general R expressions,
with separate expressions for each observation likelihood model in
multi-likelihood models. A prediction method based on fast Monte Carlo sampling
allows posterior prediction of general expressions of the latent variables.
Ecology-focused introduction in Bachl, Lindgren, Borchers, and Illian (2019)
<doi:10.1111/2041-210X.13168>.

Finn Lindgren

extract_property: Extract a summary property from all results of an inla result

Description

Usage

Arguments

Value