Calculate and Rectify Moran's I
Finds how many iterations are necessary to achieve stability in resamp...
Finds how many iterations are necessary to achieve stability in resamp...
Calculates the distance in a chessboard-alike structure.
Given a 2D data structure, it calculates the euclidean distance among ...
Computing the Local Moran's I
Calculates the manhattan distance.
Calculates the Moran's I using the algorithm proposed by Chen if(!exis...
p-value calculation.
Calculates a weighted representation of the distance matrix.
Plots the convexhull polygon from the data (latitude, longitude), and ...
Transforms a x,y position in a cartesian plane into a position in a 1D...
Calculates the expected value for local I
Scaling process for Moran's I.
Calculate the equivalence r from the I percentile in the I-Null Distri...
Loads a chessboard or matrix alike input file.
Loads a distance matrix. Instead of computing the distance from latitu...
Loads a file with latitude, longitude and variable of interest
Loads a Satellite image in PNG format
Scaling process for Local Moran's I.
Calculate a distribution of how the var of interest is correlated to a
Creates an overlay of the histogram of the data and the theorical norm...
Creates an overlay of the histogram of the data and the theorical norm...
Procrustes distance between two surfaces
Rectify I using a correlation method for all the variables in an input...
Calculates n permutations of the variable of interest to calculate n d...
Calculates n permutations of the variable of interest to calculate n d...
Performs the rescale for all the variables in an input file.
Saves a report with important statistics to describe the sample.
Standardize the input vector
Scales a matrix by column.
Calculates statistic for the received Matrix.
Calculates statistic for the received vector.
Transforms the image in the object need it to run the analysis.
Transforms the image to a matrix.
Provides a scaling method to obtain a standardized Moran's I measure. Moran's I is a measure for the spatial autocorrelation of a data set, it gives a measure of similarity between data and its surrounding. The range of this value must be [-1,1], but this does not happen in practice. This package scale the Moran's I value and map it into the theoretical range of [-1,1]. Once the Moran's I value is rescaled, it facilitates the comparison between projects, for instance, a researcher can calculate Moran's I in a city in China, with a sample size of n1 and area of interest a1. Another researcher runs a similar experiment in a city in Mexico with different sample size, n2, and an area of interest a2. Due to the differences between the conditions, it is not possible to compare Moran's I in a straightforward way. In this version of the package, the spatial autocorrelation Moran's I is calculated as proposed in Chen(2013) <arXiv:1606.03658>.