idwpred: Generate spatial predictions using inverse distance weighting...

idwpredR 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)


spm documentation built on May 6, 2022, 9:06 a.m.