ncf (version 1.1-2)

lisa.nc: Non-centered inidcators of spatial association

Description

lisa.nc is a function to estimate the (noncentred) local indicators of spatial association. The function requires multiple observations at each location. For single observations at each location use lisa

Usage

lisa.nc(x, y, z, neigh, na.rm = FALSE, resamp=1000, latlon = FALSE, quiet = FALSE)

Arguments

x

vector of length n representing the x coordinates (or latitude; see latlon).

y

vector of length n representing the y coordinates (or longitude).

z

a matrix of dimension n x p representing p (>1) observation at each location.

neigh

neighborhood size.

resamp

number of resamples under the NULL to generate p-values

latlon

Not yet implemented: if TRUE, coordinates are latitude and longitude.

na.rm

if TRUE, NA's will be dealt with through pairwise deletion of missing values.

quiet

if TRUE the counter is supressed during execution.

Value

• An object of class "lisa" is returned, consisting of the following components:
• n
  the number of pairs within each neighborhood.
• dmean
  the actual mean of distance within each neighborhood.
• correlation
  the mean correlation within the neighborhood (neigh).
• p
  the permutation two-sided p-value for each distance-class.
• coord
  a list with the x and y coordinates.

Details

This is the function to estimate the (non-centered) local indicators of spatial association modified form Anselin (1995). 'correlation' is the average correlation within a neighborhood. The function requires multiple observations at each location. Missing values are allowed -- values are assumed missing at random.

References

Anselin, L. 1995. Local indicators of spatial association - LISA. Geographical Analysis 27:93-115.

See Also

lisa plot.lisa

Examples

#first generate some sample data
    x <- expand.grid(1:20, 1:5)[,1]
    y <- expand.grid(1:20, 1:5)[,2]

#z data from an exponential random field
    z <- cbind(
        rmvn.spa(x=x, y=y, p=2, method="exp"),
        rmvn.spa(x=x, y=y, p=2, method="exp")
        )

#lisa.nc analysis
    fit1 <- lisa.nc(x=x, y=y, z=z, neigh=3)
    plot.lisa(fit1)