Comparison Vector Distribution — il_comparison

Computes the distribution of gamma patterns (agreement vectors) across record pairs. Each unique combination of gamma values across comparisons is a "comparison vector". This function counts how often each pattern occurs.

Usage

il_comparison_vectors(model, blocking = NULL, limit = NULL)

Arguments

model: A trained il_model.
blocking: A blocking rule created by block_on(). If NULL, uses all blocking rules from the model spec.
limit: Maximum number of pairs to sample. Defaults to NULL (all pairs).

Value

A tibble::tibble() with one row per unique comparison vector and columns gamma_<col> for each comparison plus count (number of pairs with that pattern) and proportion. Class il_comparison_vectors.

Details

On DuckDB/PostgreSQL, the computation runs entirely in SQL.

Examples

con <- DBI::dbConnect(duckdb::duckdb())
spec <- il_spec() |>
  il_compare(first_name, cl_exact()) |>
  il_compare(surname, cl_exact())
model <- il_model(fake_20, spec = spec, con = con)
vectors <- il_comparison_vectors(model)
ggplot2::autoplot(vectors)

il_cleanup(model)
DBI::dbDisconnect(con, shutdown = TRUE)