# lee: Compute Lee's statistic In r-spatial/spdep: Spatial Dependence: Weighting Schemes, Statistics

## 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

 `1` ```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

`lee.mc`
 ```1 2 3 4 5 6 7 8 9``` ```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) ```