| idwpred {spm} | R Documentation |
Generate spatial predictions using inverse distance weighting (IDW)
Description
This function is to make spatial predictions using inverse distance weighting.
Usage
idwpred(longlat, trainy, longlat2, nmax = 12, idp = 2, ...)
Arguments
longlat |
a dataframe contains longitude and latitude of point samples. |
trainy |
a vector of response, must have length equal to the number of rows in longlat. |
longlat2 |
a dataframe contains longitude and latitude of point locations (i.e., the centres of grids) to be predicted. |
nmax |
for a local predicting: the number of nearest observations that should be used for a prediction or simulation, where nearest is defined in terms of the space of the spatial locations. By default, 12 observations are used. |
idp |
numeric; specify the inverse distance weighting power. |
... |
other arguments passed on to gstat. |
Value
A dataframe of longitude, latitude and predictions.
Note
This function is largely based on library(gstat).
Author(s)
Jin Li
References
Pebesma, E.J., 2004. Multivariable geostatistics in S: the gstat package. Computers & Geosciences, 30: 683-691.
Examples
## Not run:
library(sp)
data(swmud)
data(sw)
idwpred1 <- idwpred(swmud[, c(1,2)], swmud[, 3], sw, nmax = 12, idp = 2)
names(idwpred1)
## End(Not run)