{
  "_id": "6a115cb8acfb0bcc41cec621",
  "Package": "Irescale",
  "Type": "Package",
  "Title": "Calculate and Rectify Moran's I",
  "Version": "2.3.0",
  "Author": "Ivan Fuentes, Thomas DeWitt, Thomas Ioerger, Michael Bishop",
  "Maintainer": "Ivan Fuentes <jivfur@tamu.edu>",
  "Description": "Provides a scaling method to obtain a standardized Moran's\nI measure. Moran's I is a measure for the spatial\nautocorrelation of a data set, it gives a measure of similarity\nbetween data and its surrounding. The range of this value must\nbe [-1,1], but this does not happen in practice. This package\nscale the Moran's I value and map it into the theoretical range\nof [-1,1]. Once the Moran's I value is rescaled, it facilitates\nthe comparison between projects, for instance, a researcher can\ncalculate Moran's I in a city in China, with a sample size of\nn1 and area of interest a1. Another researcher runs a similar\nexperiment in a city in Mexico with different sample size, n2,\nand an area of interest a2. Due to the differences between the\nconditions, it is not possible to compare Moran's I in a\nstraightforward way. In this version of the package, the\nspatial autocorrelation Moran's I is calculated as proposed in\nChen(2013) <arXiv:1606.03658>.",
  "License": "GPL (>= 2)",
  "URL": "https://github.tamu.edu/jivfur/rectifiedI",
  "Encoding": "UTF-8",
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  "Packaged": {
    "Date": "2026-05-23 07:49:08 UTC",
    "User": "root"
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  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2019-11-21 16:40:02 UTC",
  "RemoteUrl": "https://github.com/cran/Irescale",
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  "_assets": [
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    "extra/citation.json",
    "extra/citation.txt",
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    "extra/Irescale.html",
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      "date": "2019-04-15"
    },
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  "_exports": [
    "buildStabilityTable",
    "buildStabilityTableForCorrelation",
    "calculateDistMatrixFromBoard",
    "calculateEuclideanDistance",
    "calculateLocalI",
    "calculateManhattanDistance",
    "calculateMoranI",
    "calculatePvalue",
    "calculateWeightedDistMatrix",
    "convexHull",
    "coor",
    "expectedValueI",
    "iCorrection",
    "ItoPearsonCorrelation",
    "loadChessBoard",
    "loadDistanceMatrix",
    "loadFile",
    "loadSatelliteImage",
    "localICorrection",
    "nullDristribution",
    "plotHistogramOverlayCorrelation",
    "plotHistogramOverlayNormal",
    "procrustes",
    "rectifyIrho",
    "resamplingI",
    "resamplingLocalI",
    "rescaleI",
    "saveFile",
    "standardize",
    "standardizedByColumn",
    "summaryLocalIVector",
    "summaryVector",
    "transformImageToList",
    "transformImageToMatrix"
  ],
  "_help": [
    {
      "page": "buildStabilityTable",
      "title": "Finds how many iterations are necessary to achieve stability in resampling method.",
      "topics": [
        "buildStabilityTable"
      ]
    },
    {
      "page": "buildStabilityTableForCorrelation",
      "title": "Finds how many iterations are necessary to achieve stability in resampling method for rectifying I through pearson corrrelation.",
      "topics": [
        "buildStabilityTableForCorrelation"
      ]
    },
    {
      "page": "calculateDistMatrixFromBoard",
      "title": "Calculates the distance in a chessboard-alike structure.",
      "topics": [
        "calculateDistMatrixFromBoard"
      ]
    },
    {
      "page": "calculateEuclideanDistance",
      "title": "Given a 2D data structure, it calculates the euclidean distance among all the points.",
      "topics": [
        "calculateEuclideanDistance"
      ]
    },
    {
      "page": "calculateLocalI",
      "title": "Computing the Local Moran's I",
      "topics": [
        "calculateLocalI"
      ]
    },
    {
      "page": "calculateManhattanDistance",
      "title": "Calculates the manhattan distance.",
      "topics": [
        "calculateManhattanDistance"
      ]
    },
    {
      "page": "calculateMoranI",
      "title": "Calculates the Moran's I using the algorithm proposed by Chen (Chen 2013).",
      "topics": [
        "calculateMoranI"
      ]
    },
    {
      "page": "calculatePvalue",
      "title": "p-value calculation.",
      "topics": [
        "calculatePvalue"
      ]
    },
    {
      "page": "calculateWeightedDistMatrix",
      "title": "Calculates a weighted representation of the distance matrix.",
      "topics": [
        "calculateWeightedDistMatrix"
      ]
    },
    {
      "page": "convexHull",
      "title": "Plots the convexhull polygon from the data (latitude, longitude), and calculates the center of the convexhull and its area.",
      "topics": [
        "convexHull"
      ]
    },
    {
      "page": "coor",
      "title": "Transforms a x,y position in a cartesian plane into a position in a 1D array.",
      "topics": [
        "coor"
      ]
    },
    {
      "page": "expectedValueI",
      "title": "Calculates the expected value for local I",
      "topics": [
        "expectedValueI"
      ]
    },
    {
      "page": "iCorrection",
      "title": "Scaling process for Moran's I.",
      "topics": [
        "iCorrection"
      ]
    },
    {
      "page": "ItoPearsonCorrelation",
      "title": "Calculate the equivalence r from the I percentile in the I-Null Distribution.",
      "topics": [
        "ItoPearsonCorrelation"
      ]
    },
    {
      "page": "loadChessBoard",
      "title": "Loads a chessboard or matrix alike input file.",
      "topics": [
        "loadChessBoard"
      ]
    },
    {
      "page": "loadDistanceMatrix",
      "title": "Loads a distance matrix. Instead of computing the distance from latitute and longitude 'LoadDistanceMatrix' Loads the distance matrix, avoiding computing it from latitude and longitude.",
      "topics": [
        "loadDistanceMatrix"
      ]
    },
    {
      "page": "loadFile",
      "title": "Loads a file with latitude, longitude and variable of interest",
      "topics": [
        "loadFile"
      ]
    },
    {
      "page": "loadSatelliteImage",
      "title": "Loads a Satellite image in PNG format",
      "topics": [
        "loadSatelliteImage"
      ]
    },
    {
      "page": "localICorrection",
      "title": "Scaling process for Local Moran's I.",
      "topics": [
        "localICorrection"
      ]
    },
    {
      "page": "nullDristribution",
      "title": "Calculate a distribution of how the var of interest is correlated to a",
      "topics": [
        "nullDristribution"
      ]
    },
    {
      "page": "plotHistogramOverlayCorrelation",
      "title": "Creates an overlay of the histogram of the data and the theorical normal distribution.",
      "topics": [
        "plotHistogramOverlayCorrelation"
      ]
    },
    {
      "page": "plotHistogramOverlayNormal",
      "title": "Creates an overlay of the histogram of the data and the theorical normal distribution.",
      "topics": [
        "plotHistogramOverlayNormal"
      ]
    },
    {
      "page": "procrustes",
      "title": "Procrustes distance between two surfaces",
      "topics": [
        "procrustes"
      ]
    },
    {
      "page": "rectifyIrho",
      "title": "Rectify I using a correlation method for all the variables in an input file.",
      "topics": [
        "rectifyIrho"
      ]
    },
    {
      "page": "resamplingI",
      "title": "Calculates n permutations of the variable of interest to calculate n different I in order to create the Null distribution.",
      "topics": [
        "resamplingI"
      ]
    },
    {
      "page": "resamplingLocalI",
      "title": "Calculates n permutations of the variable of interest to calculate n different I in order to create the Null distribution.",
      "topics": [
        "resamplingLocalI"
      ]
    },
    {
      "page": "rescaleI",
      "title": "Performs the rescale for all the variables in an input file.",
      "topics": [
        "rescaleI"
      ]
    },
    {
      "page": "saveFile",
      "title": "Saves a report with important statistics to describe the sample.",
      "topics": [
        "saveFile"
      ]
    },
    {
      "page": "standardize",
      "title": "Standardize the input vector",
      "topics": [
        "standardize"
      ]
    },
    {
      "page": "standardizedByColumn",
      "title": "Scales a matrix by column.",
      "topics": [
        "standardizedByColumn"
      ]
    },
    {
      "page": "summaryLocalIVector",
      "title": "Calculates statistic for the received Matrix.",
      "topics": [
        "summaryLocalIVector"
      ]
    },
    {
      "page": "summaryVector",
      "title": "Calculates statistic for the received vector.",
      "topics": [
        "summaryVector"
      ]
    },
    {
      "page": "transformImageToList",
      "title": "Transforms the image in the object need it to run the analysis.",
      "topics": [
        "transformImageToList"
      ]
    },
    {
      "page": "transformImageToMatrix",
      "title": "Transforms the image to a matrix.",
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      ]
    }
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      "source": "rectifiedI.Rmd",
      "filename": "rectifiedI.html",
      "title": "Moran's I rescaling",
      "author": "Ivan Fuentes, Thomas Dewiit, Thomas Ioerger, Michael Bishop",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Performing the Analysis",
        "Rectification method 1. Three-point anisometric scaling (3-PAS)",
        "Rectified Correlation",
        "Analysis Step by Step",
        "Calculate Distance",
        "Calculate Weighted Distance Matrix",
        "Moran's I",
        "Resampling Method for I",
        "Plotting Distribution (Optional)",
        "Rectifying I",
        "Rectification method 2. Pearson Correlation",
        "Stability Analysis",
        "Rectifying to \"Max-Min\"",
        "Rectifying with correlation",
        "References"
      ],
      "created": "2019-11-21 16:40:02",
      "modified": "2019-11-21 16:40:02",
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