predict.gp {spectralGP} | R Documentation |
Prediction from a spectral GP object
Description
Produces the process values of a spectral GP object on the defined grid or predicts process values for a new set of inputs (domain points).
Usage
## S3 method for class 'gp'
predict(object,newdata=NULL,mapping=NULL,...)
Arguments
object |
A GP object, created by |
newdata |
An optional two-column matrix-like object (vector for one-dimensional data)
of locations of interest, for which the first column is the first
coordinate and the second column the second coordinate. Locations
should lie in |
mapping |
Optional output of |
... |
Other arguments. |
Details
Does prediction for a spectral GP, either at the gridpoints or
for locations by associating locations with the nearest gridpoint,
depending on the arguments supplied. If newdata
and
mapping
are both NULL, then prediction is done on the grid. If only
newdata
is supplied, the mapping is done using
new.mapping
and then the prediction is done. If mapping
is supplied (this should be done for computational efficiency if
prediction at the same locations will be done repeatedly) then the
mapping is used directly to calculate the predictions.
Value
A vector of process values (matrix for two-dimensional processes in which prediction on the grid is requested).
Author(s)
Christopher Paciorek paciorek@alumni.cmu.edu
References
Type 'citation("spectralGP")' for references.
See Also
Examples
library(spectralGP)
gp1=gp(128,matern.specdens,c(1,4))
gp2=gp(c(64,64),matern.specdens,c(1,4))
simulate(gp1)
simulate(gp2)
gridvals=predict(gp1)
gridvals2=predict(gp2)
loc1=runif(100)
loc2=cbind(runif(100),runif(100,0,1))
map1=new.mapping(gp1,loc1)
map2=new.mapping(gp2,loc2)
vals1=predict(gp1,mapping=map1)
vals2=predict(gp2,mapping=map2)
#equivalently:
vals1=predict(gp1,loc1)
vals2=predict(gp2,loc2)
plot(gp1)
points(loc1,vals1)