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Update this documentation by updating the source code. -->\n\n## MoranIndex\n\nType: [object][1]\n\n### Properties\n\n*   `moranIndex` **[number][2]** the moran's Index of the observed feature set\n*   `expectedMoranIndex` **[number][2]** the moran's Index of the random distribution\n*   `stdNorm` **[number][2]** the standard devitaion of the random distribution\n*   `zNorm` **[number][2]** the z-score of the observe samples with regard to the random distribution\n\n## moranIndex\n\nMoran's I measures patterns of attribute values associated with features.\nThe method reveal whether similar values tend to occur near each other,\nor whether high or low values are interspersed.\n\nMoran's I > 0 means a clusterd pattern.\nMoran's I < 0 means a dispersed pattern.\nMoran's I = 0 means a random pattern.\n\nIn order to test the significance of the result. The z score is calculated.\nA positive enough z-score (ex. >1.96) indicates clustering,\nwhile a negative enough z-score (ex. <-1.96) indicates a dispersed pattern.\n\nthe z-score can be calculated based on a normal or random assumption.\n\n**Bibliography**\\*\n\n1.  [Moran's I][3]\n\n2.  [pysal][4]\n\n3.  Andy Mitchell, The ESRI Guide to GIS Analysis Volume 2: Spatial Measurements & Statistics.\n\n### Parameters\n\n*   `fc` **[FeatureCollection][5]\\<any>**&#x20;\n*   `options` **[Object][1]**&#x20;\n\n    *   `options.inputField` **[string][6]** the property name, must contain numeric values\n    *   `options.threshold` **[number][2]** the distance threshold (optional, default `100000`)\n    *   `options.p` **[number][2]** the Minkowski p-norm distance parameter (optional, default `2`)\n    *   `options.binary` **[boolean][7]** whether transfrom the distance to binary (optional, default `false`)\n    *   `options.alpha` **[number][2]** the distance decay parameter (optional, default `-1`)\n    *   `options.standardization` **[boolean][7]** wheter row standardization the distance (optional, default `true`)\n\n### Examples\n\n```javascript\nconst bbox = [-65, 40, -63, 42];\nconst dataset = turf.randomPoint(100, { bbox: bbox });\n\nconst result = turf.moranIndex(dataset, {\n  inputField: 'CRIME',\n});\n```\n\nReturns **[MoranIndex][8]**&#x20;\n\n[1]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Object\n\n[2]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number\n\n[3]: https://en.wikipedia.org/wiki/Moran%27s_I\n\n[4]: http://pysal.readthedocs.io/en/latest/index.html\n\n[5]: https://tools.ietf.org/html/rfc7946#section-3.3\n\n[6]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/String\n\n[7]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Boolean\n\n[8]: #moranindex\n\n<!-- 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. -->\n\n---\n\nThis 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.\n\n### Installation\n\nInstall this single module individually:\n\n```sh\n$ npm install @turf/moran-index\n```\n\nOr install the all-encompassing @turf/turf module that includes all modules as functions:\n\n```sh\n$ npm install @turf/turf\n```\n","readmeFilename":"README.md"}