fintech-algorithms
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Dispersion, Shape, and Robust Statistics

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

In this family#

  1. Deviation, Absolute Deviation, and Squared Deviation verified

    deviationAbsoluteDeviationAndSquaredDeviation(input)
  2. Range and Interquartile Range verified

    rangeAndInterquartileRange(input)
  3. Mean Absolute Deviation verified

    meanAbsoluteDeviation(input)
  4. Median Absolute Deviation verified

    medianAbsoluteDeviation(input)
  5. Population and Sample Variance verified

    populationAndSampleVariance(input)
  6. Population and Sample Standard Deviation verified

    populationAndSampleStandardDeviation(input)
  7. Coefficient of Variation and Scale Comparability verified

    coefficientOfVariationAndScaleComparability(input)
  8. Z-Score, Robust Z-Score, and Standardization verified

    zScoreRobustZScoreAndStandardization(input)
  9. Skewness and Tail Asymmetry verified

    skewnessAndTailAsymmetry(input)
  10. Kurtosis, Excess Kurtosis, and Tail Weight verified

    kurtosisExcessKurtosisAndTailWeight(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 { deviationAbsoluteDeviationAndSquaredDeviation } from "fintech-algorithms/financial-mathematics-statistics-and-data-foundations/dispersion-shape-and-robust-statistics/deviation-absolute-deviation-and-squared-deviation";
import { rangeAndInterquartileRange } from "fintech-algorithms/financial-mathematics-statistics-and-data-foundations/dispersion-shape-and-robust-statistics/range-and-interquartile-range";

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.