Compute cell-level data-usage status for a Triangle — .compute_triangle

Internal helper that classifies every (group, cohort, dev) cell of a Triangle into one of four buckets given a fit-data filter configuration: "used", "holdout", "unused", or "future".

Mask precedence: holdout > used > unused > future.

Usage

.compute_triangle_usage(
  x,
  recent = NULL,
  regime = NULL,
  holdout = NULL,
  m_k = NULL,
  grp_m_k = NULL
)

Arguments

x: A Triangle object.
recent: Optional positive integer (calendar-diagonal cut), or NULL.
regime: Optional cohort cutoff. Accepts the same input forms handled by .resolve_regime_change_date() (NULL, Date, character, vector, or Regime).
holdout: Optional positive integer. When supplied, the last holdout calendar diagonals are flagged "holdout". The recent filter is then evaluated against the post-holdout boundary so the recent wedge sits before the holdout wedge (no overlap), matching backtest() semantics – the internal fitter operates on the masked triangle whose own max_cal is original - holdout.
m_k: Optional integer. The maturity switch as a target development index (= change of the first stable link). When both recent and regime are provided, the hybrid mask uses m_k as the boundary: cells with dev < m_k apply the cohort cut, cells with dev >= m_k apply the calendar-diagonal cut. When NULL, the hybrid logic falls back to applying both filters jointly (cohort cut AND recent cut).

Value

A data.table with one row per (group, cohort, dev) cell spanning the full triangle (observed plus future). Columns include group columns (if any), cohort, dev, .coh_rank, .cal_idx, .max_cal, is_observed, is_held_out, is_fit_data, is_excluded, and status (factor).