Alternative Fast Implementation Using Event-Based Approach

A faster implementation inspired by vecshift's event-based mechanism for collapsing consecutive employment periods.

Usage

merge_consecutive_employment_fast(dt)

Arguments

dt

A data.table output from vecshift()

Value

A data.table with collapsed consecutive employment periods

Examples

if (FALSE) { # \dontrun{
library(data.table)
library(vecshift)

# Create processed data with consecutive employment periods
employment_data <- data.table(
  id = 1:6,
  cf = rep("P001", 6),
  inizio = as.Date(c("2023-01-01", "2023-02-01", "2023-04-01",
                     "2023-05-01", "2023-08-01", "2023-10-01")),
  fine = as.Date(c("2023-01-31", "2023-03-31", "2023-04-30",
                   "2023-07-31", "2023-09-30", "2023-12-31")),
  prior = c(1, 1, 0, 0, 1, 1)
)

# Process with vecshift
processed_data <- vecshift(employment_data)

cat("Original segments:", nrow(processed_data), "\n")

# Fast merge - consolidates consecutive same-type employment
merged_fast <- merge_consecutive_employment_fast(processed_data)

cat("After fast merge:", nrow(merged_fast), "\n")
print(merged_fast[, .(cf, inizio, fine, arco, durata)])

# Compare with standard merge for validation
merged_standard <- merge_consecutive_employment(processed_data)

# Both methods should produce same number of segments
cat("\nStandard merge:", nrow(merged_standard), "segments\n")
cat("Fast merge:", nrow(merged_fast), "segments\n")
cat("Results match:", nrow(merged_fast) == nrow(merged_standard), "\n")
} # }