bm_logsumexp: Mapper for log-sum-exp aggregation

In inlabru: Bayesian Latent Gaussian Modelling using INLA and Extensions

Mapper for log-sum-exp aggregation

Description

Constructs a mapper that aggregates elements of exp(state), with optional non-negative weighting, and then takes the log(), so it can be used e.g. for v_k=\log[\sum_{i\in I_k} w_i \exp(u_i)] and v_k=\log[\sum_{i\in I_k} w_i \exp(u_i) / \sum_{i\in I_k} w_i] calculations. Relies on the input handling methods for bm_aggregate, but also allows the weights to be supplied on a logarithmic scale as log_weights. To avoid numerical overflow, it uses the common method of internally shifting the state blockwise; v_k=s_k+\log[\sum_{i\in I_k} \exp(u_i + \log(w_i)- s_k)] , where s_k=\max_{i\in I_k} u_i + \log(w_i) is the shift for block k.

Usage

bm_logsumexp(rescale = FALSE, n_block = NULL)

bru_mapper_logsumexp(...)

Arguments

rescale	logical; For bm_aggregate and bm_logsumexp, specifies if the blockwise sums should be normalised by the blockwise weight sums or not: FALSE: (default) Straight weighted sum, no rescaling. TRUE: Divide by the sum of the weight values within each block. This is useful for integration averages, when the given weights are plain integration weights. If the weights are NULL or all ones, this is the same as dividing by the number of entries in each block.
n_block	Predetermined number of output blocks. If NULL, overrides the maximum block index in the inputs. The priority order is input$n_block, the mapper definition n_block, then max(input$block).
...	Arguments passed on to bm_logsumexp()

Value

A bm_logsumexp/bm_aggregate mapper object.

See Also

bru_mapper, bru_mapper_generics

Other mappers: bm_aggregate(), bm_collect(), bm_const(), bm_expr(), bm_factor(), bm_fm_mesh_1d, bm_fmesher(), bm_harmonics(), bm_index(), bm_linear(), bm_logitaverage(), bm_marginal(), bm_matrix(), bm_multi(), bm_pipe(), bm_reparam(), bm_repeat(), bm_scale(), bm_shift(), bm_sum(), bm_taylor(), bru_get_mapper(), bru_mapper()

Examples

m <- bm_logsumexp()
ibm_eval2(m, list(block = c(1, 2, 1, 2), weights = 1:4), 11:14)
ibm_eval2(m, list(block = c(1, 2, 1, 2), weights = 1:4, n_block = 3), 11:14)

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