fintech-algorithms
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Estimator Bias, Consistency, Efficiency, and Robustness

Install and import#

bash
npm install fintech-algorithms
ts
import { estimatorBiasConsistencyEfficiencyAndRobustness } from "fintech-algorithms/financial-mathematics-statistics-and-data-foundations/sampling-estimation-and-statistical-inference/estimator-bias-consistency-efficiency-and-robustness";

Signature#

estimatorBiasConsistencyEfficiencyAndRobustness(input)

Worked example#

verified This is the worked example published in the article, replayed by the test suite on every run. The output cannot drift.

Input#

input
{
  "sample": [2, 3, 4, 3, 4],
  "estimates": [3, 3.1, 3.2, 3.3, 3.4],
  "populationMean": 3.2,
  "alpha": 0.05,
  "mseBenchmark": 0.1,
  "nullMean": 3,
  "alternativeMean": 3.5,
  "practicalThreshold": 0.1,
  "comparisons": 5
}

Call#

estimatorBiasConsistencyEfficiencyAndRobustness(input)

Returns#

object with 2 fields: bias, mse

{
  "bias": 0,
  "mse": 0.019999999999999983
}

Diagrams#

Estimator Bias, Consistency, Efficiency, and Robustness — article hero
Estimator Bias, Consistency, Efficiency, and Robustness — calculation ledger
Estimator Bias, Consistency, Efficiency, and Robustness — concept anatomy
Estimator Bias, Consistency, Efficiency, and Robustness — failure boundary
Estimator Bias, Consistency, Efficiency, and Robustness — method map
Estimator Bias, Consistency, Efficiency, and Robustness — scenario contrast

How it works#

This page states the contract — how to call it correctly. The article explains the concept: why it works, and where it breaks.

Read the article →

References#

The rest of the Sampling, Estimation, and Statistical Inference family#