100 lines
3.4 KiB
Markdown
100 lines
3.4 KiB
Markdown
# @turf/moran-index
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<!-- Generated by documentation.js. Update this documentation by updating the source code. -->
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## MoranIndex
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Type: [object][1]
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### Properties
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* `moranIndex` **[number][2]** the moran's Index of the observed feature set
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* `expectedMoranIndex` **[number][2]** the moran's Index of the random distribution
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* `stdNorm` **[number][2]** the standard devitaion of the random distribution
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* `zNorm` **[number][2]** the z-score of the observe samples with regard to the random distribution
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## moranIndex
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Moran's I measures patterns of attribute values associated with features.
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The method reveal whether similar values tend to occur near each other,
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or whether high or low values are interspersed.
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Moran's I > 0 means a clusterd pattern.
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Moran's I < 0 means a dispersed pattern.
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Moran's I = 0 means a random pattern.
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In order to test the significance of the result. The z score is calculated.
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A positive enough z-score (ex. >1.96) indicates clustering,
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while a negative enough z-score (ex. <-1.96) indicates a dispersed pattern.
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the z-score can be calculated based on a normal or random assumption.
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**Bibliography**\*
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1. [Moran's I][3]
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2. [pysal][4]
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3. Andy Mitchell, The ESRI Guide to GIS Analysis Volume 2: Spatial Measurements & Statistics.
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### Parameters
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* `fc` **[FeatureCollection][5]\<any>** 
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* `options` **[Object][1]** 
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* `options.inputField` **[string][6]** the property name, must contain numeric values
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* `options.threshold` **[number][2]** the distance threshold (optional, default `100000`)
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* `options.p` **[number][2]** the Minkowski p-norm distance parameter (optional, default `2`)
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* `options.binary` **[boolean][7]** whether transfrom the distance to binary (optional, default `false`)
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* `options.alpha` **[number][2]** the distance decay parameter (optional, default `-1`)
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* `options.standardization` **[boolean][7]** wheter row standardization the distance (optional, default `true`)
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### Examples
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```javascript
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const bbox = [-65, 40, -63, 42];
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const dataset = turf.randomPoint(100, { bbox: bbox });
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const result = turf.moranIndex(dataset, {
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inputField: 'CRIME',
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});
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```
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Returns **[MoranIndex][8]** 
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[1]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Object
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[2]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number
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[3]: https://en.wikipedia.org/wiki/Moran%27s_I
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[4]: http://pysal.readthedocs.io/en/latest/index.html
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[5]: https://tools.ietf.org/html/rfc7946#section-3.3
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[6]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/String
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[7]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Boolean
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[8]: #moranindex
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<!-- This file is automatically generated. Please don't edit it directly. If you find an error, edit the source file of the module in question (likely index.js or index.ts), and re-run "yarn docs" from the root of the turf project. -->
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---
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This module is part of the [Turfjs project](https://turfjs.org/), an open source module collection dedicated to geographic algorithms. It is maintained in the [Turfjs/turf](https://github.com/Turfjs/turf) repository, where you can create PRs and issues.
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### Installation
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Install this single module individually:
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```sh
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$ npm install @turf/moran-index
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```
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Or install the all-encompassing @turf/turf module that includes all modules as functions:
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```sh
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$ npm install @turf/turf
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```
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