ibm_eval_methods: Specific 'ibm_eval' method implementations

In inlabru: Bayesian Latent Gaussian Modelling using INLA and Extensions

Specific ibm_eval method implementations

Description

Specific ibm_eval() method implementations.

Usage

## S3 method for class 'bm_taylor'
ibm_eval(mapper, input = NULL, state = NULL, ...)

## S3 method for class 'bm_const'
ibm_eval(mapper, input, state = NULL, ...)

## S3 method for class 'bm_shift'
ibm_eval(mapper, input, state = NULL, ...)

## S3 method for class 'bm_scale'
ibm_eval(mapper, input, state = NULL, ...)

## S3 method for class 'bm_aggregate'
ibm_eval(mapper, input, state = NULL, ...)

## S3 method for class 'bm_logsumexp'
ibm_eval(mapper, input, state = NULL, log = TRUE, ...)

## S3 method for class 'bm_logitaverage'
ibm_eval(mapper, input, state = NULL, logit = TRUE, ...)

## S3 method for class 'bm_marginal'
ibm_eval(mapper, input, state = NULL, ..., reverse = FALSE)

## S3 method for class 'bm_pipe'
ibm_eval(mapper, input, state = NULL, ...)

## S3 method for class 'bm_multi'
ibm_eval(
  mapper,
  input,
  state = NULL,
  inla_f = FALSE,
  ...,
  jacobian = NULL,
  pre_A = deprecated()
)

## S3 method for class 'bm_reparam'
ibm_eval(mapper, input, state = NULL, ..., jacobian = NULL)

## S3 method for class 'bm_collect'
ibm_eval(
  mapper,
  input,
  state,
  inla_f = FALSE,
  multi = FALSE,
  ...,
  sub_lin = NULL
)

## S3 method for class 'bm_expr'
ibm_eval(
  mapper,
  input,
  state = NULL,
  ...,
  derived = NULL,
  data = NULL,
  data_mask = NULL,
  .envir = rlang::caller_env()
)

## S3 method for class 'bm_repeat'
ibm_eval(mapper, input, state, multi = FALSE, ..., sub_lin = NULL)

## S3 method for class 'bm_sum'
ibm_eval(mapper, input, state, multi = FALSE, ..., sub_lin = NULL)

Arguments

mapper	A mapper S3 object, inheriting from bru_mapper.
input	Data input for the mapper.
state	A vector of latent state values for the mapping, of length ibm_n(mapper, inla_f = FALSE)
...	Arguments passed on to other methods
log	logical; control log output. Default TRUE, see the ibm_eval() details for logsumexp mappers.
logit	logical; control logit output. Default TRUE, see the ibm_eval() details for logitaverage mappers.
reverse	logical; control bm_marginal evaluation. Default FALSE. When TRUE, reverses the direction of the mapping, see details for marginal mappers.
inla_f	logical; when TRUE for ibm_n() and ibm_values(), the result must be compatible with the INLA::f(...) and corresponding INLA::inla.stack(...) constructions. For ⁠ibm_{eval,jacobian,linear}⁠, the input interpretation may be different. Implementations do not normally need to do anything different, except for mappers of the type needed for hidden multicomponent models such as "bym2", which can be handled by bm_collect.
jacobian	For ibm_eval() methods, an optional pre-computed Jacobian, typically supplied by internal methods that already have the Jacobian.
pre_A	in favour of jacobian.
multi	logical; If TRUE (or positive), recurse one level into sub-mappers
sub_lin	Internal, optional pre-computed sub-mapper information
derived	The state vectors of variables derived from the root variables. If NULL or missing, defaults to an empty list.
data	should be a list with data objects, with the main object called data; see bm_expr() for details.
data_mask	A data mask object to use for evaluating the expression. If NULL or missing, a data mask will be constructed with bru_data_mask() from the data, state, derived, and .envir arguments. This can be used to avoid redundant construction of the data mask when evaluating different expressions multiple times with the same input and state.
.envir	The environment in which to evaluate the expression. By default, this is set to the caller environment.

Functions

• ibm_eval(bm_taylor): Evaluates linearised mapper information at the given state. The input argument is ignored, so that the usual argument order ibm_eval(mapper, input, state) syntax can be used, but also ibm_eval(mapper, state = state). For a mapper with a named jacobian list, the state argument must also be a named list. If state is NULL, all-zero is assumed.

• ibm_eval(bm_const): Returns the input values, with NA replaced by 0.

• ibm_eval(bm_logsumexp): When log is TRUE (default), ibm_eval() for logsumexp returns the log-sum-weight-exp value. If FALSE, the sum-weight-exp value is returned.

• ibm_eval(bm_logitaverage): When logit is TRUE (default), ibm_eval() for logitaverage returns the logit-sum-weight-inverse-logit value. If FALSE, the sum-weights=invere-logit value is returned.

• ibm_eval(bm_marginal): When xor(mapper[["inverse"]], reverse) is FALSE, ibm_eval() for marginal returns qfun(pnorm(x), param), evaluated in a numerically stable way. Otherwise, evaluates the inverse qnorm(pfun(x, param)) instead.

• ibm_eval(bm_expr): Accepts a state list with named entries, one for each variable. The input and data formats should match the description given for bm_expr().

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