ibm_inla_subset: Find index subset of INLA visible states

In inlabru: Bayesian Latent Gaussian Modelling using INLA and Extensions

Find index subset of INLA visible states

Description

Implementations must return a logical vector of TRUE/FALSE for the subset such that, given the full A matrix and values output, A[, subset, drop = FALSE] and values[subset] (or values[subset, , drop = FALSE] for data.frame values) are equal to the inla_f = TRUE version of A and values. The default method uses the ibm_values output to construct the subset indexing.

Usage

ibm_inla_subset(mapper, ...)

## Default S3 method:
ibm_inla_subset(mapper, ...)

Arguments

mapper	A mapper S3 object, inheriting from bru_mapper.
...	Arguments passed on to other methods

Value

A logical vector of TRUE/FALSE for the subset such that, given the full A matrix and values output, A[, subset, drop = FALSE] and values[subset] (or values[subset, , drop = FALSE] for data.frame values) are equal to the inla_f = TRUE version of A and values.

Methods (by class)

• ibm_inla_subset(default): Uses the [ibm_values⁠()] output to construct the inla subset indexing as the difference between ⁠inla_f=FALSEandinla_f=TRUE⁠. Extra arguments such as ⁠multi⁠are passed on to [ibm_values()]. This means it supports both regular vector values and⁠multi=1' data.frame values.

See Also

Other mapper methods: bru_mapper_generics, ibm_as_taylor(), ibm_eval(), ibm_eval2(), ibm_invalid_output(), ibm_is_linear(), ibm_is_rowwise(), ibm_jacobian(), ibm_n(), ibm_n_output(), ibm_names(), ibm_simplify(), ibm_values()

Examples

m <- bm_collect(list(A = bm_linear(), B = bm_linear()), hidden = TRUE)
ibm_inla_subset(m)

inlabru documentation built on July 28, 2026, 9:07 a.m.