make_stable_integration_points

mesh

<code>inla.mesh.segment</code> defining the integration domain

number of subdivision points along each triangle edge, giving
<code>(nsub + 1)^2</code> proto-integration points used to compute
the vertex weights
(default <code>NULL=9</code>, giving 100 integration points for each triangle)

nsub

Basic robust integration weights for mesh/polygon intersections

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

inlabru

make_stable_integration_points: Basic robust integration weights for mesh/polygon intersections

Description

Usage

Arguments

Value