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Convenience function that handles the common case of updating a spatial distribution with vector-based observations. Combines the functionality of transform_pmf, transform_likelihood, and update_pmf into a single workflow.

Usage

rasterize_demand(
  x,
  value_col,
  prior = NULL,
  template = NULL,
  density = FALSE,
  standardize = FALSE
)

Arguments

x

SpatVector containing observations

value_col

Character name of column containing values

prior

Optional SpatRaster prior PMF (if NULL, uses uniform prior)

template

SpatRaster template (required if prior = NULL)

density

Logical; if TRUE return density surface

standardize

Logical; if TRUE standardize likelihood values

Value

SpatRaster containing posterior PMF or density surface

Examples

if (FALSE) { # \dontrun{
# Basic usage with uniform prior
result1 <- rasterize_demand(
  case_spatial,
  value_col = "cases",
  template = pop
)

# With population-based prior
prior <- transform_pmf(pop)
result2 <- rasterize_demand(
  case_spatial,
  value_col = "cases",
  prior = prior,
  density = TRUE
)
} # }