I am stumped by a failure of idw() to produce valid values for var1.var,
the weighted squared distance. Here is my rather basic script:
data(meuse)
data(meuse.grid)
# 1. Convert Sampled Points (meuse) to SpatialPointsDataFrame (sp
format for gstat)
meuse_sp <- meuse
coordinates(meuse_sp) <- ~x+y
proj4string(meuse_sp) <- CRS("+init=epsg:28992")
# 2. Convert Prediction Grid (meuse.grid) to SpatialPixelsDataFrame
# (sp format for gstat and prediction)
meuse_grid_sp <- meuse.grid
coordinates(meuse_grid_sp) <- ~x+y
gridded(meuse_grid_sp) <- TRUE # Define it as a regular grid
proj4string(meuse_grid_sp) <- CRS("+init=epsg:28992")
# We use the idw() function directly for IDW
idw_zinc <- idw(log(zinc) ~ 1, # Interpolate log(zinc) with
a constant mean (~1)
meuse_sp, # Using the sampled data
newdata = meuse_grid_sp, # Predicting onto the grid
idp = 2.0) # Inverse Distance Power = 2
head(idw_zinc@data) var1.pred var1.var
1 6.257014 NA
2 6.399096 NA
3 6.300862 NA
4 6.213336 NA
5 6.647233 NA
6 6.482221 NA
What am I missing here? How can prediction values be produced but the error
values not?
Cheers,
Jochen
Dr. Jochen Albrecht, GISP (he/him/his)
Department of Geography and Environmental Science
<http://www.geo.hunter.cuny.edu/>
Hunter College CUNY
695 Park Avenue
New York, NY 10065
Member, Board of Directors, GIS Certification Institute
<https://www.gisci.org/>
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