bru_fill_missing: Fill in missing values in Spatial grids

In inlabru: Bayesian Latent Gaussian Modelling using INLA and Extensions

Fill in missing values in Spatial grids

Description

Computes nearest-available-value imputation for missing values in space

Usage

bru_fill_missing(
  data,
  where,
  values,
  layer = NULL,
  selector = NULL,
  batch_size = deprecated()
)

Arguments

data	A SpatialPointsDataFrame, SpatialPixelsDataFrame, SpatialGridDataFrame, SpatRaster, Raster, or sf object containing data to use for filling
where	A, matrix, data.frame, or SpatialPoints or SpatialPointsDataFrame, or sf object, containing the locations of the evaluated values
values	A vector of values to be filled in where is.na(values) is TRUE
layer, selector	Specifies what data column or columns from which to extract data, see bru_comp() for details.
batch_size	due to improved algorithm. Size of nearest-neighbour calculation blocks, to limit the memory and computational complexity.

Value

An infilled vector of values

Examples

## Not run: 
if (require("sf", quietly = TRUE)) {
  points <-
    sf::st_as_sf(
      data.frame(
        x = 1:3,
        y = 4:6,
        val = c(NA, NA, NA)
      ),
      coords = c("x", "y")
    )
  input_coord <- expand.grid(x = 0:7, y = 0:7)
  input <-
    sf::st_as_sf(
      cbind(input_coord, val = as.vector(input_coord$y)),
      coords = c("x", "y")
    )
  points$val <- bru_fill_missing(input, points, points$val)
  print(points)

  # To fill in missing values in a grid:
  print(input$val[c(3, 30)])
  input$val[c(3, 30)] <- NA # Introduce missing values
  input$val <- bru_fill_missing(input, input, input$val)
  print(input$val[c(3, 30)])
}

## End(Not run)

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