NEWS

r4subrisk 0.3.1

Add risk_monte_carlo(), which puts uncertainty on the FMEA scores. An RPN is built from three integer judgements, so a single number hides how confident the assessment is. The simulation samples each probability, impact, and detectability around its assessed value and reports the distribution of RPN, per risk and for the register as a whole, including a 90% interval and the probability that each risk is actually critical. The random state is set and restored per call when a seed is given, so results are reproducible without disturbing the caller's RNG.

Add risk_reduction_summary(), which quantifies the risk removed between two registers: total and mean RPN reduction, percentage reduction, and counts of risks reduced, downgraded, added, and resolved.
Add plot_risk_heatmap() and risk_heatmap_data() for the standard FMEA probability by impact heatmap, with an optional interactive plotly version.
Add a pluggable risk-model interface: risk_model() plus the pre-built risk_model_fmea(), risk_model_probability_impact(), and risk_model_ich_q9(). apply_risk_model() scores any set of risks to a normalized 0-100 value so alternative models feed the same Risk pillar.
Add vignette: "Case study: FMEA risk on a pilot submission", a worked before-and-after mitigation walkthrough using the example risk register from r4subdata.
Clarified the package DESCRIPTION: "R4SUB" expands to "Ready for Submission" (previously "R for Regulatory Submission", inconsistent with the rest of the ecosystem).

Add vignette: "Risk Management with r4subrisk" covering create_risk_register(), compute_risk_scores(), apply_mitigations(), compare_risk_registers(), and evidence_to_risks() integration.