codisp.ks {SpatialPack} | R Documentation |
A Nadaraya-Watson Codispersion Coefficient
Description
Computes a nonparametric version of the codispersion coefficient between two spatial variables using a Nadaraya-Watson estimator.
Usage
codisp.ks(x, y, coords, lags, kernel = "epanech", bandwidths)
Arguments
x |
an |
y |
an |
coords |
an |
lags |
a 2D vector of spatial lags. |
kernel |
character string which determines the smoothing kernel. |
bandwidths |
a 3D vector with the kernel bandwidth smoothing parameters. |
Details
The procedure computes the codispersion coefficient for two spatial variables which is based on a Nadaraya-Watson version of the codispersion coefficient through a suitable kernel.
Value
A vector with the semivariogram for each variable, the crossed semivariogram and the codispersion coefficient.
References
Cuevas, F., Porcu, E., Vallejos, R. (2013). Study of spatial relationships between two sets of variables: A nonparametric approach. Journal of Nonparametric Statistics 25, 695-714.
Vallejos, R., Osorio, F., Bevilacqua, M. (2020). Spatial Relationships Between Two Georeferenced Variables: With Applications in R. Springer, Cham.
Examples
# Pinus Radiata dataset
data(radiata)
# defining basal-area and height variables from the Pinus Radiata dataset
x <- radiata$basal
y <- radiata$height
# extracting the coordinates from Pinus Radiata dataset
coords <- radiata[,1:2]
# computing the codispersion coefficient
bwds <- c(174, 247, 187)
cf <- codisp.ks(x, y, coords, lags = c(200,200), kernel = "epanech", bandwidths = bwds)
cf