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Generate log posterior predictive density from a geostatistical surface onto point data

Source: R/validation_functions.R
log_posterior_density.Rd

Generate log posterior predictive density from a geostatistical surface onto point data

Usage

log_posterior_density(draws, validation_data, id_raster, na.rm = FALSE)

Arguments

draws

(matrix) A predictive draw matrix, where each row corresponds to a pixel in the id_raster and each column corresponds to one sampled estimate of the outcome.

validation_data

(data.frame) Table containing at least the following fields:

  • x (numeric) location x position, in the same projection as id_raster

  • y (numeric) location y position, in the same projection as id_raster

  • indicator (integer) The number of events in the population

  • samplesize (integer) The total population, denominator for indicator

id_raster

(terra::SpatRaster) Raster showing the sample study area, created using build_id_raster.

na.rm

(logical(1), default FALSE) Should NA values be omitted from the LPD calculation?

Value

(numeric(1)) Log predictive density of the validation data given the draw estimates.

Details

Calculated across draws. Requires an ID raster to match each point observation to a set of draws. Assumes binomial data.

For examples, see vignette('model-comparison', package = 'mbg')