fix: add submodule

.gitmodules

@@ -0,0 +1,3 @@
+[submodule "src/aggregation"]
+	path = src/aggregation
+	url = ./src/aggregation/

index.js

@@ -5,7 +5,7 @@ import {
   geometricMeanOfOdds,
   extremizedGeometricMeanOfOdds,
   neyman,
-} from "@forecasting/aggregation";
+} from "./src/aggregation/index.js";
 
 export {
   median,

node_modules/.package-lock.json

@@ -1,13 +0,0 @@
-{
-  "name": "forecasting",
-  "version": "0.0.1",
-  "lockfileVersion": 2,
-  "requires": true,
-  "packages": {
-    "node_modules/@forecasting/aggregation": {
-      "version": "0.0.1",
-      "resolved": "https://registry.npmjs.org/@forecasting/aggregation/-/aggregation-0.0.1.tgz",
-      "integrity": "sha512-N6NwJaHioyJQZwjvbNYQCknegrQoWne5I1TILA0jSu+8xkCIN+16cYumc1hZSYAKTzfBsiQWXZbuubfVMpgXFg=="
-    }
-  }
-}

node_modules/@forecasting/aggregation/README.md

@@ -1,55 +0,0 @@
-## About
-
-![](decision-method.png)
-
-This package contains a series of utilities for forecast aggregation. It is currently in _alpha_, meaning that the code itself works, but there isn't error checking.
-
-For an introduction to different aggregation methods, see Jaime Sevilla's [Aggregation](https://forum.effectivealtruism.org/s/hjiBqAJNKhfJFq7kf) series. For an explanation of the neyman method, see [here](https://forum.effectivealtruism.org/s/hjiBqAJNKhfJFq7kf/p/biL94PKfeHmgHY6qe).
-
-## Built with
-
-- vanilla javascript
-- [Best readme template](https://github.com/othneildrew/Best-README-Template)
-
-## Getting started
-
-### Installation
-
-```sh
-npm install @forecasting/aggregation
-```
-
-### Usage
-
-```js
-import {
-  median,
-  arithmeticMean,
-  geometricMean,
-  geometricMeanOfOdds,
-  extremizedGeometricMeanOfOdds,
-  neyman,
-} from "@forecasting/aggregation";
-
-let ps = [0.1, 0.2, 0.4, 0.5];
-console.log(ps);
-
-console.log(median(ps));
-console.log(arithmeticMean(ps));
-console.log(geometricMean(ps));
-console.log(geometricMeanOfOdds(ps));
-console.log(extremizedGeometricMeanOfOdds(ps, 1.5)); // 1.5 is the extremization factor
-console.log(extremizedGeometricMeanOfOdds(ps, 2.5));
-console.log(neyman(ps));
-```
-
-## Roadmap
-
-- [ ] validate probabilities (must be 0<= p <=1)
-- [ ] Decide on a return type if probabilities are not validated (-1? / null?)
-- [ ] Write wrapper code for validation
-- [ ] Validate that array.length > 0
-- [ ] add weighting? by recency?
-- [ ] filter outliers?
-- [ ] Write documentation
-- [ ] Do another repository for scoring methods

node_modules/@forecasting/aggregation/index.js

@@ -1,64 +0,0 @@
-// Helpers
-const sum = (array) => array.reduce((a, b) => a + b, 0);
-const probabilityToOdds = (p) => p / (1 - p);
-const oddsToProbability = (o) => o / (1 + o);
-
-// Main functions
-export const median = (array) => {
-  // needs validation array not empty
-  let midway = Math.floor(array.length);
-  let arrayToBeSorted = [...array];
-  // sorting mutates the array, which I am averse to
-  let arraySorted = arrayToBeSorted.sort((a, b) => a - b);
-  if (midway % 2) {
-    return arraySorted[midway];
-  } else {
-    return (arraySorted[midway - 1] + arraySorted[midway]) / 2;
-  }
-};
-
-export const arithmeticMean = (array) => {
-  let result = sum(array) / array.length;
-  return result;
-};
-
-export const geometricMean = (array) => {
-  // sum of logs seems more numerically stable than multiplying a lot of numbers 0<=p<=1
-  let arrayAsLog = array.map((p) => Math.log(p));
-  let sumOfLogs = sum(arrayAsLog) / arrayAsLog.length;
-  let result = Math.exp(sumOfLogs);
-  return result;
-};
-
-export const geometricMeanOfOdds = (array) => {
-  let arrayOfOdds = array.map((p) => probabilityToOdds(p));
-  let arrayOfLogsOfOdds = arrayOfOdds.map((p) => Math.log(p));
-  let sumOfLogsOfOdds = sum(arrayOfLogsOfOdds) / arrayOfLogsOfOdds.length;
-  let geomMeanOfOdds = Math.exp(sumOfLogsOfOdds);
-  let result = oddsToProbability(geomMeanOfOdds);
-  return result;
-};
-
-export const extremizedGeometricMeanOfOdds = (
-  array,
-  extremizationParameter = 1.5
-) => {
-  let arrayOfOdds = array.map((p) => probabilityToOdds(p));
-  let arrayOfLogsOfOdds = arrayOfOdds.map((p) => Math.log(p));
-  let extremizedSumOfLogsOfOdds =
-    (extremizationParameter * sum(arrayOfLogsOfOdds)) /
-    arrayOfLogsOfOdds.length;
-  let extremizedGeomMeanOfOdds = Math.exp(extremizedSumOfLogsOfOdds);
-  let result = oddsToProbability(extremizedGeomMeanOfOdds);
-  return result;
-};
-
-export const neyman = (array) => {
-  let n = array.length;
-
-  let d =
-    (n * (Math.sqrt(3 * Math.pow(n, 2) - 3 * n + 1) - 2)) /
-    (Math.pow(n, 2) - n - 1);
-  let result = extremizedGeometricMeanOfOdds(array, d);
-  return result;
-};

node_modules/@forecasting/aggregation/package.json

@@ -1,18 +0,0 @@
-{
-  "name": "@forecasting/aggregation",
-  "version": "0.0.1",
-  "description": "Forecasting aggregation utilities",
-  "main": "index.js",
-  "scripts": {
-    "test": "node test.js"
-  },
-  "keywords": [
-    "forecasting",
-    "aggregation",
-    "prediction",
-    "prediction",
-    "markets"
-  ],
-  "author": "Nuño Sempere",
-  "license": "MIT"
-}

node_modules/@forecasting/aggregation/tests.js

@@ -1,19 +0,0 @@
-import {
-  median,
-  arithmeticMean,
-  geometricMean,
-  geometricMeanOfOdds,
-  extremizedGeometricMeanOfOdds,
-  neyman,
-} from "./index.js";
-
-let ps = [0.1, 0.2, 0.4, 0.5];
-console.log(ps);
-
-console.log(median(ps));
-console.log(arithmeticMean(ps));
-console.log(geometricMean(ps));
-console.log(geometricMeanOfOdds(ps));
-console.log(extremizedGeometricMeanOfOdds(ps, 1.5));
-console.log(extremizedGeometricMeanOfOdds(ps, 2.5));
-console.log(neyman(ps));

src/aggregation

@@ -0,0 +1 @@
+Subproject commit 359897cc5221b0f6ee2f428484daa05253a94364