lisa.nc: Non-centered indicators of spatial association

In ncf: Spatial Covariance Functions

Non-centered indicators of spatial association

Description

lisa.nc is a function to estimate the (non-centred) multivariate 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 = 999,
  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.
na.rm	If TRUE, NA's will be dealt with through pairwise deletion of missing values.
resamp	number of resamples under the NULL to generate p-values
latlon	If TRUE, coordinates are latitude and longitude.
quiet	If TRUE, the counter is suppressed during execution.

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, and pairwise complete observations will be used.

Value

An object of class "lisa" is returned, consisting of the following components:

correlation	the mean correlation within the neighborhood (neigh).
p	the permutation two-sided p-value for each distance-class.
n	the number of pairs within each neighborhood.
dmean	the actual mean of distance within each neighborhood.
coord	a list with the x and y coordinates.

Author(s)

Ottar N. Bjornstad [e-mail]

References

Anselin, L. 1995. Local indicators of spatial association - LISA. Geographical Analysis 27:93-115. <doi:10.1111/j.1538-4632.1995.tb00338.x>

See Also

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)
## Not run: plot(fit1)

ncf documentation built on May 7, 2022, 5:05 p.m.