Matematica e statistica universali
Methods for cross-domain on the Julia and TypeScript compute planes.
38 capabilities
26 of 38 have a bound kernel or engine. States are shown as the registry records them; a request fails closed wherever an adapter, specialist model or governed data is still missing.
| Metodo | Capability ID | Stato | Viene eseguito su |
|---|---|---|---|
| Robust Distribution | risk.capability.universal-mathematics-statistics.robust.distribution.v1 |
Reference implementation | Julia · frontier_risk_math.robust_distribution |
| Empirical Distribution | risk.capability.universal-mathematics-statistics.empirical.distribution.v1 |
Reference implementation | Python · stats.empirical_distribution |
| Bayesian Updating | risk.capability.universal-mathematics-statistics.bayesian.updating.v1 |
Reference implementation | Julia · frontier_risk_math.beta_binomial |
| Hierarchical Bayesian | risk.capability.universal-mathematics-statistics.hierarchical.bayesian.v1 |
Adapter required | – |
| Extreme Value | risk.capability.universal-mathematics-statistics.extreme.value.v1 |
Reference implementation | – |
| Tail Risk | risk.capability.universal-mathematics-statistics.tail.risk.v1 |
Reference implementation | Python · tail.pot_gpd |
| Copula Dependency | risk.capability.universal-mathematics-statistics.copula.dependency.v1 |
Adapter required | – |
| Tail Dependence | risk.capability.universal-mathematics-statistics.tail.dependence.v1 |
Adapter required | Python · dependence.tail_empirical |
| Monte Carlo | risk.capability.universal-mathematics-statistics.monte.carlo.v1 |
Reference implementation | Python · simulation.monte_carlo |
| Latin Hypercube | risk.capability.universal-mathematics-statistics.latin.hypercube.v1 |
Reference implementation | Python · sampling.latin_hypercube |
| Importance Sampling | risk.capability.universal-mathematics-statistics.importance.sampling.v1 |
Reference implementation | Python · sampling.importance |
| Sequential Monte Carlo | risk.capability.universal-mathematics-statistics.sequential.monte.carlo.v1 |
Adapter required | – |
| Kalman Filter | risk.capability.universal-mathematics-statistics.kalman.filter.v1 |
Adapter required | – |
| Extended Kalman | risk.capability.universal-mathematics-statistics.extended.kalman.v1 |
Adapter required | – |
| Unscented Kalman | risk.capability.universal-mathematics-statistics.unscented.kalman.v1 |
Adapter required | – |
| Particle Filter | risk.capability.universal-mathematics-statistics.particle.filter.v1 |
Adapter required | – |
| Markov Chain | risk.capability.universal-mathematics-statistics.markov.chain.v1 |
Adapter required | Python · markov.transition |
| Hidden Markov | risk.capability.universal-mathematics-statistics.hidden.markov.v1 |
Adapter required | – |
| Change Point | risk.capability.universal-mathematics-statistics.change.point.v1 |
Reference implementation | Python · change.cusum |
| Anomaly Detection | risk.capability.universal-mathematics-statistics.anomaly.detection.v1 |
Reference implementation | Python · anomaly.robust_mad |
| Survival Analysis | risk.capability.universal-mathematics-statistics.survival.analysis.v1 |
Adapter required | Python · survival.kaplan_meier |
| Reliability | risk.capability.universal-mathematics-statistics.reliability.v1 |
Adapter required | Python · reliability.weibull |
| Fault Tree | risk.capability.universal-mathematics-statistics.fault.tree.v1 |
Adapter required | – |
| Event Tree | risk.capability.universal-mathematics-statistics.event.tree.v1 |
Adapter required | – |
| Bayesian Network | risk.capability.universal-mathematics-statistics.bayesian.network.v1 |
Adapter required | – |
| Information Theory | risk.capability.universal-mathematics-statistics.information.theory.v1 |
Reference implementation | Python · information.mutual_information |
| Entropy and Concentration | risk.capability.universal-mathematics-statistics.entropy.and.concentration.v1 |
Reference implementation | Julia · frontier_risk_math.concentration |
| Correlation | risk.capability.universal-mathematics-statistics.correlation.v1 |
Reference implementation | Python · stats.correlation |
| Regression | risk.capability.universal-mathematics-statistics.regression.v1 |
Adapter required | Python · regression.ols |
| Gaussian Process | risk.capability.universal-mathematics-statistics.gaussian.process.v1 |
Adapter required | Python · gaussian_process.rbf |
| Spatial Statistics | risk.capability.universal-mathematics-statistics.spatial.statistics.v1 |
Adapter required | Python · spatial.morans_i |
| Geostatistics | risk.capability.universal-mathematics-statistics.geostatistics.v1 |
Adapter required | Python · geostatistics.ordinary_kriging |
| Bootstrap | risk.capability.universal-mathematics-statistics.bootstrap.v1 |
Reference implementation | Python · stats.bootstrap_mean_ci |
| Global Sensitivity | risk.capability.universal-mathematics-statistics.global.sensitivity.v1 |
Connected | Python · sensitivity.sobol_outputs |
| Shapley Sensitivity | risk.capability.universal-mathematics-statistics.shapley.sensitivity.v1 |
Adapter required | Python · sensitivity.shapley_coalitions |
| Optimisation under Uncertainty | risk.capability.universal-mathematics-statistics.optimization.under.uncertainty.v1 |
Adapter required | Python · optimization.robust_minimax |
| Multi-Criteria Decision | risk.capability.universal-mathematics-statistics.multi.criteria.decision.v1 |
Adapter required | Python · decision.weighted_mcda |
| Real Options | risk.capability.universal-mathematics-statistics.real.options.v1 |
Adapter required | Python · decision.real_option_binomial |
Methods, data and supports
- Method families
- robust statistics, Bayesian inference, extreme value, Monte Carlo, copula dependence, stochastic process, time series, change detection, survival reliability, spatial statistics, geostatistics, optimisation, decision analysis, information theory
- Domini
- cross-domain
- Compute planes
- Julia, TypeScript
- Source classes
- governed-observations, sealed-risk-data-cut
- Spatial supports
- point, object, grid, region, network
- Temporal supports
- instant, series, window, scenario
Propose a method
New methods are registered with a stable ID and a hand-derived golden test.
Stato
La metodologia, la struttura e le definizioni di The Global Risks Index sono una bozza di lavoro preparatoria (2026), diffusa per esame e commenti e non destinata all’attuazione. Nessun valore compare finché un’edizione non viene pubblicata a partire da un taglio di evidenze regolamentato; i valori riporteranno allora intervalli, classi, fonti e il relativo percorso di correzione. I simulatori applicano i metodi pubblicati ai numeri che scegli e non mostrano mai un valore NXS-GRX.
Che cosa non è NXS-GRX
NXS-GRX è un'informazione di ricerca e di analisi del rischio. Non è un rating creditizio o ESG e non usa alcuna scala di rating, non è un indice di riferimento per strumenti finanziari, non è una statistica ufficiale, non è un allerta di emergenza né una classificazione ufficiale e non è una consulenza. Non deve essere usato per valutare persone fisiche. Le classi di rischio sono fasce su una scala pubblicata, mai graduatorie di paesi o persone.
Istituzioni e fonti
The Nexus Consortium is stewarded by three independent not-for-profit institutions: The Global Centre for Risk and Innovation (GCRI), through GCRI US in Washington, DC and GCRI Canada in Ontario, with GCRI Canada as Lead Institution, Consortium Secretariat and lead contracting organisation; The Global Risks Forum (GRF); and The Global Risks Alliance (GRA). Technology, infrastructure and service providers work with the Consortium at arm’s length under written agreements, like every other external party in the public-private-planet model, and hold no role in its stewardship.
Ogni valore riporta l’attribuzione delle proprie fonti, che mantengono le rispettive licenze. I nomi esterni sono citati unicamente a fini di interoperabilità. I testi redatti da Nexus sono destinati alla licenza CC BY 4.0 al momento della pubblicazione.
Avis en français
La méthodologie et les définitions du NXS-GRX sont un projet de travail préparatoire (2026). Le NXS-GRX est une information de recherche et d’analyse des risques : ni notation, ni indice de référence financier, ni statistique officielle, ni alerte, ni conseil. Les classes de risque sont des bandes sur une échelle publiée, non des classements.