56 lines
1.5 KiB
Markdown
56 lines
1.5 KiB
Markdown
## About
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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.
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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).
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## Built with
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- vanilla javascript
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- [Best readme template](https://github.com/othneildrew/Best-README-Template)
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## Getting started
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### Installation
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```sh
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npm install @forecasting/aggregation
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```
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### Usage
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```js
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import {
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median,
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arithmeticMean,
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geometricMean,
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geometricMeanOfOdds,
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extremizedGeometricMeanOfOdds,
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neyman,
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} from "@forecasting/aggregation";
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let ps = [0.1, 0.2, 0.4, 0.5];
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console.log(ps);
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console.log(median(ps));
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console.log(arithmeticMean(ps));
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console.log(geometricMean(ps));
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console.log(geometricMeanOfOdds(ps));
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console.log(extremizedGeometricMeanOfOdds(ps, 1.5)); // 1.5 is the extremization factor
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console.log(extremizedGeometricMeanOfOdds(ps, 2.5));
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console.log(neyman(ps));
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```
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## Roadmap
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- [ ] validate probabilities (must be 0<= p <=1)
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- [ ] Decide on a return type if probabilities are not validated (-1? / null?)
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- [ ] Write wrapper code for validation
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- [ ] Validate that array.length > 0
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- [ ] add weighting? by recency?
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- [ ] filter outliers?
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- [ ] Write documentation
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- [ ] Do another repository for scoring methods
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