Evaluate or sample from a posterior result given a model and locations
Source:R/model.R
evaluate_model.Rd
Evaluate or sample from a posterior result given a model and locations
Usage
evaluate_model(
model,
state,
data = NULL,
input = NULL,
comp_simple = NULL,
predictor = NULL,
format = NULL,
used = NULL,
n_pred = NULL,
...
)
evaluate_state(
model,
result,
property = "mode",
n = 1,
seed = 0L,
num.threads = NULL,
internal_hyperpar = FALSE,
...
)
Arguments
- model
A bru model
- state
list of state lists, as generated by
evaluate_state()
- data
A
list
,data.frame
, orSpatial*DataFrame
, with coordinates and covariates needed to evaluate the predictor.- input
Precomputed inputs list for the components
- comp_simple
Precomputed
comp_simple_list
for the components- predictor
A formula or an expression to be evaluated given the posterior or for each sample thereof. The default (
NULL
) returns adata.frame
containing the sampled effects. In case of a formula the right hand side is used for evaluation.- format
character; determines the storage format of predictor output. Available options:
"auto"
If the first evaluated result is a vector or single-column matrix, the "matrix" format is used, otherwise "list"."matrix"
A matrix where each column contains the evaluated predictor expression for a state."list"
A list where each element contains the evaluated predictor expression for a state.
- used
A
bru_used()
object, or NULL (default)- n_pred
integer. If provided, scalar predictor results are expanded to vectors of length
n_pred
.- ...
Additional arguments passed on to
inla.posterior.sample
- result
- property
Property of the model components to obtain value from. Default: "mode". Other options are "mean", "0.025quant", "0.975quant", "sd" and "sample". In case of "sample" you will obtain samples from the posterior (see
n
parameter). Ifresult
isNULL
, all-zero vectors are returned for each component.- n
Number of samples to draw.
- seed
If seed != 0L, the random seed
- num.threads
Specification of desired number of threads for parallel computations. Default NULL, leaves it up to INLA. When seed != 0, overridden to "1:1"
- internal_hyperpar
logical; If
TRUE
, return hyperparameter properties on the internal scale. Currently ignored whenproperty="sample"
. Default isFALSE
.