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They preserve missingness and separate later restatements from actual emergence. Shared A/E arithmetic now lives in core. See `docs/reference/review-forecasts.md` in the private repository.\n\n`resolveHistoricalInformationSet` selects declared immutable input versions using availability evidence and exact dependencies. Missing dates require an explicit retrospective policy or an unavailable result. Its catalog-level assurance does not certify a full historical fold; see `docs/reference/historical-information.md` in the private repository.\n\n`prepareHistoricalReview` connects selected configuration to actual loss/exposure revision clocks and the existing recipe engine. `runHistoricalFold` and `runHistoricalStudy` compose dated policy/assumption bindings, explicit prior calibration, frozen forecasts and scoring. Tuning uses, unavailable folds and changes to fixed assumptions remain visible; holdout independence is not inferred.\n\nPure, framework-free P&C actuarial math for TypeScript. It includes triangles, deterministic and stochastic reserving, trends/on-leveling, limits and ILFs, discounting, and generalized definition-driven casualty diagnostics.\n\nThe SDK 0.16 `selectDevelopmentPattern` and `replayDevelopmentSelection` APIs\nbind explicit averaging/tail intent to native calculations and versioned\nassumptions. The same operation feeds review graphs and factor-intent\nsensitivities, including monthly and quarterly origin windows. See\n`docs/reference/review-development-selection.md` in the private repository.\n\nThe SDK 0.16 `createSelectedEstimateRange` and\n`replaySelectedEstimateRange` APIs retain finite ordered endpoints with exactly\nmatching quantity semantics, exact supporting result references, rationale,\nauthorship and optional caller-declared materiality. The contract identifies a\nhuman-selected nonprobabilistic range; it does not manufacture a predictive\ninterval or choose the actuarial judgment.\n\nThe SDK 0.16 `tailFitting` capability exposes `fitDevelopmentPatternTail`\nthrough that same selection calculation and replay artifact. It requires an\nexplicit curve family, fit window, regular period-index convention and horizon.\nInvalid fits keep the selected tail unavailable; truncated fits retain warnings.\nFitting does not invent adoption or predictive uncertainty.\n\nThe SDK 0.16 `calculateReviewOnLevel` API binds earned monetary premium to\nexplicit earning intervals, a target date and historically available rate\nhistory. Its calculated factors feed BF/Cape Cod, selection, reconciliation,\nsensitivity and historical scoring through the shared review graph. Annual\npolicy terms and uniform writing/earning remain required. Model-derived BF\nprior calibration on adjusted premium needs a separate denominator contract\nand is explicitly unsupported. See `docs/reference/review-foundations.md` in\nthe private repository for clocks, missingness and exact replay requirements.\n\nThe SDK 0.16 `calculateReviewLayerApplication`, `calibrateReviewIlf` and\n`applyReviewIlf` APIs connect exact claim, occurrence or policy financial-term\nevidence to fitted or versioned-table layer restoration and a broader-basis\norigin series. Complete population and membership detail are required; an\naggregate triangle is not substituted. Calculated outputs can enter selection\nthrough exact replay. Source authenticity and uncertainty propagation remain\nexplicitly unavailable. See `docs/reference/review-capping-ilf.md` in the\nprivate repository.\n\nThe SDK 0.16 `frequencySeverity` model uses explicit reported-count and\nloss-per-count patterns, tails, count definitions and paired source clocks.\nBoth component fits and actual observation maturities remain visible. A missing\ncurrent loss leaves current unpaid unavailable. Count/scaled severity quantities,\nhistorical catalog bindings, graph selection/reconciliation and portable replay\nuse the same connected review contracts. Combined uncertainty is unavailable;\nemergence forecasting requires an explicit pattern convention.\n\nThe SDK 0.16 connected `munichChainLadder` model binds exact paid and incurred\nsources to the existing Quarg–Mack kernel. It requires identical dated grids and\nmissing masks, both source revisions, an explicit final-column sigma policy and\nno tail. Both native projections and their factor/ratio/residual sample counts\nremain visible; the declared primary basis feeds comparison, selection and\npaid reconciliation. True cumulative age zero is always zero and stays outside\nthe fit. Prediction-error uncertainty is explicitly unavailable. See\n`docs/reference/review-munich-chain-ladder.md` in the private repository.\n\nThe SDK 0.16 connected `caseOutstanding` model binds exact cumulative paid\nand point-in-time case sources to an adopted complete case run-off,\npaid-on-prior-case and terminal payout pattern. It projects from the latest\njoint observation, keeps missing origins unavailable, qualifies negative case\nor recovery positions under explicit policies and retains the native payment\npath. True cumulative age zero is numeric zero by definition; origin ID `\"0\"`\nis ordinary. Deterministic uncertainty remains unavailable. See\n`docs/reference/review-case-outstanding.md` in the private repository.\n\nThe SDK 0.16 connected `fisherLange` model binds exact cumulative paid and\ncumulative closed-count sources to adopted ultimate counts, a complete unit-sum\ndisposal pattern and a common annual severity trend. It requires a regular\ncontiguous origin/development cadence, projects from the latest joint maturity,\nrejects count reversals and needed ages without observed severity, and governs\nnegative paid increments explicitly. True cumulative age zero is numeric zero\nby definition; origin ID `\"0\"` remains an ordinary cohort label. The result\nretains native age evidence and exact effective assumptions; deterministic\nuncertainty remains unavailable. See `docs/reference/review-fisher-lange.md` in\nthe private repository.\n\nThe SDK 0.16 `calibrateReviewUlae` and `calculateReviewUlaeReserve` APIs bind\nthe native Conger–Nolibos calculations to exact calendar sources, disjoint loss\nand expense bases, explicit populations, versioned activity weights and a\nversioned selected ratio. Expected, Bornhuetter–Ferguson and development forms\npreserve missing origin inputs and their native activity components. A replayed\nexpense reserve can enter selection as calculated evidence. Source membership\nand uncertainty remain explicit limitations. See\n`docs/reference/review-ulae.md` in the private repository.\n\nThe SDK 0.16 `calculateReviewDiscounting` API replays a nominal unpaid origin\nseries, ties explicit valuation-relative cash flows to every available amount,\nand applies versioned annual-effective flat or spot rates through the native\npresent-value kernel. Intended purpose, discount/accounting dates, payout and\nrate sources, timing convention, curve-horizon policy and risk-margin treatment\nremain inspectable. Nominal and discounted quantities stay side by side; an\nexplicit risk margin stays outside every total. See\n`docs/reference/review-discounting.md` in the private repository.\n\nThe package is designed to support the actuary's compliance with the ASOPs; it does not make a work product compliant and is not “ASOP-approved.” The credentialed actuary remains responsible for data, assumptions, selections, review, and communication.\n\nThe SDK 0.16 connected workflow has a tested public consumer at\n`examples/reserve-review` in the private repository. It demonstrates annual\npremium and quarterly vehicle-year inputs, raw-grid normalization inside the\nreplayed graph, CL/BF/Cape Cod/Mack comparison, explicit cohort weighting and\npaid reconciliation. Its synthetic assumptions are separate from the existing\nMack literature example; unavailable evidence and blend uncertainty stay visible.\n\nThe source repository is private, so the guide and reference links below open only with repository access. The published package is unaffected and remains Apache-2.0.\n\nSDK 0.8 adds versioned loss history, irregular period and exposure contracts,\npopulation statistics, shared financial terms, and deterministic recipe and\nscenario execution. See the 0.8 adoption guide (`docs/migrations/0.8-reusable-customization.md`)\nand customization reference (`docs/reference/reusable-customization.md`).\n\n## Install\n\n```bash\nnpm install @actuarial-ts/core@0.16.0\n```\n\nESM, TypeScript-first, zero runtime dependencies, Node 20+.\n\n## Reserving quick start\n\n```ts\nimport { buildTriangles, computeDevelopmentFactors, runChainLadder, runMack } from \"@actuarial-ts/core\";\n\nconst { paid } = buildTriangles(claimSnapshots, { cadence: \"annual\", asOfDate: \"2025-12-31\" });\nconst selected = computeDevelopmentFactors(paid).averages.find((item) => item.spec.key === \"all-wtd\")!.values;\nconst chainLadder = runChainLadder(paid, { selected, tailFactor: 1.02 });\nconst mack = runMack(paid, { selected, tailFactor: 1.02 });\n```\n\nUnobservable triangle cells are `null`. Volume-weighted factors are sum/sum over rows where both cells exist. CDFs multiply right-to-left, tail last. Missing, zero, or negative divisors yield `null`, never `NaN`.\n\n## Generalized diagnostics\n\nThe model deliberately separates five concerns:\n\n1. A measure declares source, quantity kind, unit, development semantics, sum aggregation, missingness, and its population/basis.\n2. A formula template declares reusable arithmetic over typed roles.\n3. An instance binds formula roles to measure expressions.\n4. Calculation identity covers arithmetic, bindings, and all dependent measure/population/basis semantics.\n5. Presentation and review rules remain visible in full definition identity without pretending to change the arithmetic.\n\n```ts\nimport {\n  CASUALTY_FORMULA_TEMPLATES,\n  compileDiagnosticDefinition,\n  createCasualtyMetricInstances,\n  prepareDiagnosticData,\n  runMetricDiagnostics,\n} from \"@actuarial-ts/core\";\n\nconst instances = createCasualtyMetricInstances({\n  counts: { reported: \"reported\", open: \"open\", closedNoPay: \"closed-no-pay\", closedWithPay: \"closed-with-pay\" },\n  exposure: \"earned-vehicle-years\",\n  amountBindings: [\n    { id: \"gross\", paid: \"gross-paid\", incurred: \"gross-incurred\" },\n    { id: \"primary-250k\", paid: \"primary-paid\", incurred: \"primary-incurred\" },\n  ],\n});\n\nconst compiled = compileDiagnosticDefinition({\n  diagnosticDefinitionVersion: \"1.0.0\",\n  id: \"fleet-diagnostics\",\n  version: \"1.0.0\",\n  lossRowGrain: \"aggregate\",\n  measures,\n  countPopulations,\n  exposureBases,\n  amountBases,\n  derivedMeasures: [],\n  formulas: CASUALTY_FORMULA_TEMPLATES,\n  instances,\n  reviewRules,\n  periodAxis,\n});\n\nconst prepared = prepareDiagnosticData({ definition: compiled, losses, exposures });\nconst result = runMetricDiagnostics({ prepared, groupMap: { fleet: \"all-fleet\" } });\n```\n\n### Eager and compact paths\n\nThe example above uses the retained eager APIs. The additive compact APIs,\nintroduced in 0.7.0, expose the same numeric views while retaining complete audit\nand identity evidence behind authenticated owners instead of eagerly expanding\nit. Choose matching preparation, calculation, and maturity functions:\n\n| Operation | Eager | Compact |\n|---|---|---|\n| Prepare inputs | `prepareDiagnosticData` | `prepareDiagnosticDataCompact` |\n| Calculate metric views | `runMetricDiagnostics` | `runMetricDiagnosticsCompact` |\n| Select one development age | `sameMaturity` | `sameMaturityCompact` |\n| Select the latest common age across output groups | `commonMaturity` | `commonMaturityCompact` |\n\nThe original maturity signatures remain unchanged; compact results use the\nseparately named helpers, not casts to eager results. Development ages use the\nresult's declared age unit. Review evaluations are available through\n`pageDiagnosticReviewEvaluations`, with source references separately available\nthrough `pageDiagnosticReviewEvaluationSources`. Passing and not-evaluated\nevaluations remain available; paging is not sampling.\n\nUse owner-controlled identity documents and `iterateDiagnosticIdentityJson`\nwhen complete canonical text is needed. `materializePreparedDiagnosticData` and\n`materializeMetricDiagnosticsResult` intentionally expand the eager evidence;\nthey are explicit compatibility choices, not a memory-saving export path.\nCloning or parsing an owner does not recreate its authority. Compact storage is\nnot a dataset-capacity or bounded-memory guarantee for an entire application.\n\nSDK 0.8 adds authenticated compact selection helpers for metric, source-group,\nwhole-origin, and valuation/age scopes. Eligible clean aggregate preparations\nshare immutable cells while preserving the same fresh preparation and result\nidentities; an ineligible scope returns `undefined` so the data gateway can use\nordinary preparation. These functions do not issue review or execution receipts.\n\nThese are lower-level calculation APIs. For a host import or analysis boundary\nthat enforces both review and metric execution policy, use the validated gateway\nin `@actuarial-ts/data`. The runnable compact adoption guide (`docs/migrations/0.7-compact-diagnostics.md`)\ncovers the complete workflow and streamed replay (`docs/reference/diagnostic-replay-stream.md`).\n\nThe six built-in formulas are basis-independent. The factory creates ten count instances plus six per amount basis (`10 + 6 × basisCount`): one basis produces 16, two produce 22. A `$250K`, primary, gross, net, or ceded calculation is represented by caller-declared amount measures and a structured `AmountBasisDefinition`; it does not need a separate capped formula. Claim-level caps use `claim-layer` derivations before aggregation. Pre-limited external values record their source/transformation instead of implying the SDK recreated an unavailable claim-level operation.\n\nAll metrics are ratio-of-sums: measures are aggregated at source-group/origin/valuation, groups are mapped and merged, then division happens once. Measure-local `missing: \"unknown\" | \"zero\"` is explicit. Exposure timing is either `origin-static` or `valuation-specific`. Calendar and ordered axes derive normalized origins, valuations, development ages, and units; input rows cannot assert a trusted age.\n\nExposure reconciliation accepts at most 250,000 observations per call. Collection\ncapacity is independent of optional source-file/sheet/cell metadata: each record\nretains the JSON depth (256 including the outer array) and one-million-node\nresource guards, while the owned result is frozen by observation/cohort rather\nthan rechecked against a single collection-wide JSON node budget. Malformed\narrays, accessors, non-JSON metadata, and cycles still produce typed validation\nerrors. Nonfinite exposure values remain supported audited inputs, not usable\nnumeric exposure values. This is a bounded capacity, not an unlimited scale claim.\n\nCompilation validates the whole graph atomically: IDs, sources, role types, compatibility groups, development semantics, derivation acyclicity, expression limits, rule operands, basis/population references, and period coordinates. Authentic compiled/prepared objects are owner-branded and frozen. Formula, calculation, definition, preparation, and result identities are deterministic FNV-1a/JCS integrity aids—not cryptographic signatures.\n\nSee the generated formula and instance catalog (`docs/reference/diagnostic-formulas.md`) and 0.6 migration guide (`docs/migrations/0.6-generalized-diagnostics.md`).\n\n## Main method families\n\n- Reserving: chain ladder, Mack, Bornhuetter-Ferguson, Benktander, Cape Cod/Gluck, Expected Claims, frequency-severity, Fisher-Lange, Munich chain ladder, Clark, ODP bootstrap, and Merz-Wüthrich one-year risk.\n- Adjustments: Berquist-Sherman, salvage/subrogation, ULAE, tails, trends, premium on-leveling, discounting, capping, severity models, and ILFs.\n- Infrastructure: triangle algebra, seeded RNG, RFC 8785 canonical JSON, integrity tags, traditional triangle diagnostics, and generalized metric diagnostics.\n\nPublished-value tests are the numerical contract. A reserving math change is not acceptable until those fixtures still pass.\n\n## License\n\nApache-2.0. See LICENSE and NOTICE.\n\nSDK 0.9 adds native post-aggregation formulas and correct financial currency units.\nSee the 0.9 migration guide (`docs/migrations/0.9-analysis-expressions.md`).\n\n## Composite history sources\n\nSDK 0.10 adds multiple original artifacts within one claim namespace, explicit\ncomposite identity selectors and complete input-artifact membership checks.\nUpgrade the five SDK packages together and preserve the producing runtime\nwith archived evidence. See the 0.10 migration guide (`docs/migrations/0.10-composite-history.md`).\n\n## Connected reserve review\n\nSDK 0.16 adds the typed source-to-publication review contracts. Development age\nzero is the structural cumulative origin and always has value 0; a nonzero first\nobservation must use its positive elapsed age. Upgrade all five SDK packages\ntogether and retain earlier runtimes with archived evidence. See the 0.16\nmigration guide (`docs/migrations/0.16-connected-reserve-review.md`).\n","readmeFilename":"README.md"}