R: Compute Lee's statistic

lee {spdep} | R Documentation

## Compute Lee's statistic

### Description

A simple function to compute Lee's L statistic for bivariate spatial data;

L(x,y) = (n sum_i (sum_j w_ij (x_i - xbar)) (sum_j w_ij (y_j - ybar))) / (S2 sqrt(sum_i (x_i - xbar)^2)) sqrt(sum_i (x_i - xbar)^2))

### Usage

    lee(x, y, listw, n, S2, zero.policy=NULL, NAOK=FALSE)

### Arguments

`x` | a numeric vector the same length as the neighbours list in listw
`y` | a numeric vector the same length as the neighbours list in listw
`listw` | a `listw` object created for example by `nb2listw`
`n` | number of zones
`S2` | Sum of squared sum of weights by rows.
`zero.policy` | default NULL, use global option value; if TRUE assign zero to the lagged value of zones without neighbours, if FALSE assign NA
`NAOK` | if 'TRUE' then any 'NA' or 'NaN' or 'Inf' values in x are passed on to the foreign function. If 'FALSE', the presence of 'NA' or 'NaN' or 'Inf' values is regarded as an error.

### Value

a list of

`L` | Lee's L statistic
`local L` | Lee's local L statistic

### Author(s)

Roger Bivand and Virgiio GÃ³mez-Rubio Virgilio.Gomez@uclm.es

### References

Lee (2001). Developing a bivariate spatial association measure: An integration of Pearson's r and Moran's I. J Geograph Syst 3: 369-385

### See Also

`lee.mc`

### Examples

    data(boston, package="spData")
    lw<-nb2listw(boston.soi)

    x<-boston.c$CMEDV
    y<-boston.c$CRIM
    z<-boston.c$RAD

    Lxy<-lee(x, y, lw, length(x), zero.policy=TRUE)
    Lxz<-lee(x, z, lw, length(x), zero.policy=TRUE)

[Package spdep version 1.2-2 Index]