Changelog

Source: NEWS.md

lossratio (development version)

Initial development release. Long-format experience-data toolkit for long-term health insurance loss-ratio analysis.

Core API

• Experience class: as_experience(), is_experience(), check_experience(), add_experience_period().
• Aggregation: build_triangle() (cohort × dev), build_calendar() (calendar period), build_total() (portfolio total).
• Age-to-age: build_ata(), fit_ata(), S3 summary() on ATA / ATAFit, find_ata_maturity().
• Exposure-driven: build_ed(), fit_ed(), S3 summary() on ED / EDFit.
• Projection: fit_cl() (chain ladder, basic / mack), fit_lr() (loss-ratio with sa / ed / cl methods).
• Diagnostics: detect_cohort_regime() (regime detection across underwriting cohorts), backtest() (calendar-diagonal hold-out, supports both fit_cl and fit_lr).
• Visualisation: S3 plot() and plot_triangle() methods on every fit class.

Dataset

• experience — 33,480-row fully synthetic example data, generated by data-raw/make_experience.R.

Documentation

• Seven vignettes covering getting started, aggregation frameworks, chain ladder, loss-ratio projection methods, triangle / ata diagnostics, regime detection, and backtesting.