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Estimates the probability that two randomly selected records from the dataset are a match, using deterministic rules and a recall assumption. This prior anchors the Fellegi-Sunter model before more detailed parameter estimation.

Usage

il_estimate_prior(model, ..., recall = 0.7, profile_sql = FALSE)

Arguments

model

An il_model object (piped in).

...

Blocking rules created by block_on() that define deterministic matching criteria.

recall

A numeric value between 0 and 1 representing the assumed recall of the deterministic rules. Defaults to 0.7.

profile_sql

Logical. If TRUE, store lightweight SQL timing metadata in model$params$sql_profile.

Value

An updated il_model with the estimated prior.

Examples

df <- data.frame(
  unique_id = 1:20,
  first_name = c(
    'John', 'Jon', 'Jane', 'Jane', 'Bob',
    'Bobby', 'Alice', 'Alicia', 'Tom', 'Thomas',
    'John', 'Jon', 'Jane', 'Janet', 'Bob',
    'Robert', 'Alice', 'Alison', 'Tom', 'Tomas'
  ),
  surname = c(
    'Smith', 'Smith', 'Doe', 'Doe', 'Jones',
    'Jones', 'Brown', 'Brown', 'White', 'White',
    'Smith', 'Smyth', 'Doe', 'Doe', 'Jones',
    'Jones', 'Brown', 'Browne', 'White', 'White'
  ),
  dob = c(
    '1990-01-01', '1990-01-01', '1985-06-15', '1985-06-15',
    '2000-12-01', '2000-12-01', '1975-03-22', '1975-03-22',
    '1988-07-04', '1988-07-04', '1990-01-01', '1990-01-02',
    '1985-06-15', '1985-06-16', '2000-12-01', '2000-12-02',
    '1975-03-22', '1975-03-23', '1988-07-04', '1988-07-05'
  ),
  city = c(
    'London', 'London', 'Paris', 'Paris', 'Berlin',
    'Berlin', 'Rome', 'Rome', 'Madrid', 'Madrid',
    'London', 'London', 'Paris', 'Paris', 'Berlin',
    'Berlin', 'Rome', 'Rome', 'Madrid', 'Madrid'
  ),
  email = c(
    'john@example.com', 'jon@example.com', 'jane@example.com',
    'jane@example.com', 'bob@example.com', 'bobby@example.com',
    'alice@example.com', 'alicia@example.com', 'tom@example.com',
    'thomas@example.com', 'john@example.com', 'jon@example.com',
    'jane@example.com', 'janet@example.com', 'bob@example.com',
    'robert@example.com', 'alice@example.com', 'alison@example.com',
    'tom@example.com', 'tomas@example.com'
  )
)
con <- DBI::dbConnect(duckdb::duckdb())
spec <- il_spec() |>
  il_compare(first_name, cl_jaro_winkler(0.9, 0.7)) |>
  il_compare(surname, cl_jaro_winkler(0.9, 0.7)) |>
  il_compare(dob, cl_exact()) |>
  il_block_on(surname) |>
  il_block_on(first_name)
model <- il_model(df, spec = spec, con = con)

model <- il_estimate_prior(model, block_on(first_name, surname, dob))
DBI::dbDisconnect(con, shutdown = TRUE)