predict.inla_metric_graph_spde {MetricGraph}

Predict method for 'inlabru' fits on Metric Graphs

Description

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,
  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,
  ...,
  data = deprecated()
)

Arguments

object

An inla_metric_graph_spde object built with the graph_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 if euclidean, the user must provide a data frame with the first column being the x Euclidean coordinates and the second column being the y 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 if data_coords is euclidean.

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.

...

Additional arguments passed on to inla.posterior.sample().

data

Use newdata instead.

Value

A list with predictions.