fintech-algorithms
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Data, Variables, Samples, and Measurement

10 algorithms in Financial Mathematics, Statistics, and Data Foundations · 10 with asserted arithmetic.

In this family#

  1. Observations, Entities, Variables, and Datasets verified

    observationsEntitiesVariablesAndDatasets(input)
  2. Numeric, Categorical, Ordinal, and Binary Variables verified

    numericCategoricalOrdinalAndBinaryVariables(input)
  3. Population, Sample, Census, and Sampling Frame verified

    populationSampleCensusAndSamplingFrame(input)
  4. Cross-Sectional, Time-Series, Panel, and Event Data verified

    crossSectionalTimeSeriesPanelAndEventData(input)
  5. Identifiers, Keys, Joins, and Data Grain verified

    identifiersKeysJoinsAndDataGrain(input)
  6. Timestamps, Time Zones, Calendars, and Observation Time verified

    timestampsTimeZonesCalendarsAndObservationTime(input)
  7. Missing, Nonfinite, Censored, and Truncated Values verified

    missingNonfiniteCensoredAndTruncatedValues(input)
  8. Measurement Error, Resolution, Accuracy, and Precision verified

    measurementErrorResolutionAccuracyAndPrecision(input)
  9. Revisions, Vintages, and Point-in-Time Availability verified

    revisionsVintagesAndPointInTimeAvailability(input)
  10. Data Provenance, Lineage, Ownership, and Licensing verified

    dataProvenanceLineageOwnershipAndLicensing(input)

What they share#

Every topic here is a record-transform, so once you have called one the rest follow the same shape. Import paths differ only in the final segment:

ts
import { observationsEntitiesVariablesAndDatasets } from "fintech-algorithms/financial-mathematics-statistics-and-data-foundations/data-variables-samples-and-measurement/observations-entities-variables-and-datasets";
import { numericCategoricalOrdinalAndBinaryVariables } from "fintech-algorithms/financial-mathematics-statistics-and-data-foundations/data-variables-samples-and-measurement/numeric-categorical-ordinal-and-binary-variables";

Read them in the order above — the sequence is pedagogical, not alphabetical.

Where this sits#

Financial Mathematics, Statistics, and Data Foundations collects 120 algorithms across 12 families. For the concept behind this family rather than the call signatures, see the concept guides.