Changes in version 0.2.0 (2026-04-03)                  

New features

  - Pipe-friendly API: lfq_fit(), lfq_advantage(), lfq_forecast(),
    lfq_score() enable tidyverse-style chaining with |>.
  - Engine registry: register_engine() / unregister_engine() allow
    third-party packages to register custom modeling engines, similar to
    the parsnip engine system.
  - lfq_summary(): One-row-per-lineage overview combining growth rates,
    confidence intervals, and relative Rt in a single tibble.
  - as.data.frame.lfq_data(): Clean tibble export for interoperability.

Improvements

  - fit_model() now accepts both built-in and registered engine names.
  - lfq_engines() lists all available engines including custom
    registrations.
  - 251 unit tests (up from 243 in v0.1.0).

                        Changes in version 0.1.0                        

  - Initial CRAN release.