# iCorrection: Scaling process for Moran's I. In Irescale: Calculate and Rectify Moran's I

## Description

iCorrection . consists in centering the I value (I-median) and scaling by the difference between the median and 1st or 99th quantile. The correction is according to the following equation:

I = ≤ft\{ \begin{array}{lr} \frac{(I-median)}{(median - Q1)}& I < median\\ \frac{(I-median)}{(Q99-median)}& I>median\\ \end{array}\right\}

## Usage

 1 iCorrection(I, vI, statsVI, scalingUpTo = "Quantile", sd = 1) 

## Arguments

 I Moran's I, It could be computed using calculateMoranI function. vI the vector obtained by resamplingI. statsVI the statistic vector obtained from summaryVector. scalingUpTo the rescaling could be done up to the 0.01% and 99.9% quantile or max and min values. The two possible options are: "MaxMin", or "Quantile". The default value for this parameter is Quantile. sd this represents upto which standard deviation you want to scale I

rescaled I

## Examples

 1 2 3 4 5 6 7 inputFileName<-system.file("testdata", "chen.csv", package="Irescale") input<-loadFile(inputFileName) distM<-calculateEuclideanDistance(input$data) I<-calculateMoranI(distM = distM,varOfInterest = input$varOfInterest) vI<-resamplingI(distM, input\$varOfInterest) statsVI<-summaryVector(vI) corrections<-iCorrection(I,vI,scalingUpTo="Quantile") 

Irescale documentation built on Nov. 22, 2019, 1:07 a.m.