Predict method for 'inlabru' fits on Metric Graphs
Source:R/graph_spde.R
predict.inla_metric_graph_spde.Rd
Auxiliar function to obtain predictions of the field using 'inlabru'.
Usage
# S3 method for class 'inla_metric_graph_spde'
predict(
object,
cmp,
bru_fit,
newdata = NULL,
formula = NULL,
data_coords = c("PtE", "euclidean"),
normalized = TRUE,
repl = NULL,
repl_col = NULL,
group = NULL,
group_col = NULL,
n.samples = 100,
seed = 0L,
probs = c(0.025, 0.5, 0.975),
return_original_order = TRUE,
num.threads = NULL,
include = NULL,
exclude = NULL,
drop = FALSE,
tolerance_merge = 1e-05,
...,
data = deprecated()
)
Arguments
- object
An
inla_metric_graph_spde
object built with thegraph_spde()
function.- cmp
The 'inlabru' component used to fit the model.
- bru_fit
A fitted model using 'inlabru' or 'INLA'.
- newdata
A data.frame of covariates needed for the prediction. The locations must be normalized PtE.
- formula
A formula where the right hand side defines an R expression to evaluate for each generated sample. If NULL, the latent and hyperparameter states are returned as named list elements. See Details for more information.
- data_coords
It decides which coordinate system to use. If
PtE
, the user must provide the locations as a data frame with the first column being the edge number and the second column as the distance on edge, otherwise ifeuclidean
, the user must provide a data frame with the first column being thex
Euclidean coordinates and the second column being they
Euclidean coordinates.- normalized
if
TRUE
, then the distances in distance on edge are assumed to be normalized to (0,1). Default TRUE. Will not be used ifdata_coords
iseuclidean
.- repl
Which replicates? If there is no replicates, one can set
repl
toNULL
. If one wants all replicates, then one sets torepl
to.all
.- repl_col
Column containing the replicates. If the replicate is the internal group variable, set the replicates to ".group". If not replicates, set to
NULL
.- group
Which groups? If there is no groups, one can set
group
toNULL
. If one wants all groups, then one sets togroup
to.all
.- group_col
Which "column" of the data contains the group variable?
- n.samples
Integer setting the number of samples to draw in order to calculate the posterior statistics. The default is rather low but provides a quick approximate result.
- seed
Random number generator seed passed on to
inla.posterior.sample()
- probs
A numeric vector of probabilities with values in the standard unit interval to be passed to stats::quantile
- return_original_order
Should the predictions be returned in the original order?
- 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"
- include
Character vector of component labels that are needed by the predictor expression; Default: NULL (include all components that are not explicitly excluded)
- exclude
Character vector of component labels that are not used by the predictor expression. The exclusion list is applied to the list as determined by the include parameter; Default: NULL (do not remove any components from the inclusion list)
- drop
logical; If keep=FALSE, data is a SpatialDataFrame, and the prediciton summary has the same number of rows as data, then the output is a SpatialDataFrame object. Default FALSE.
- tolerance_merge
Tolerance for merging prediction points into original points to increase stability.
- ...
Additional arguments passed on to
inla.posterior.sample()
.- data