| eval_basis | R Documentation |
Evaluate basis functions at points or average functions over polygons.
eval_basis(basis, s)
## S4 method for signature 'Basis,matrix'
eval_basis(basis, s)
## S4 method for signature 'Basis,SpatialPointsDataFrame'
eval_basis(basis, s)
## S4 method for signature 'Basis,SpatialPolygonsDataFrame'
eval_basis(basis, s)
## S4 method for signature 'Basis,STIDF'
eval_basis(basis, s)
## S4 method for signature 'TensorP_Basis,matrix'
eval_basis(basis, s)
## S4 method for signature 'TensorP_Basis,STIDF'
eval_basis(basis, s)
## S4 method for signature 'TensorP_Basis,STFDF'
eval_basis(basis, s)
basis |
object of class |
s |
object of class |
This function evaluates the basis functions at isolated points, or averages
the basis functions over polygons, for computing the matrix S. The latter
operation is carried out using Monte Carlo integration with 1000 samples per polygon. When
using space-time basis functions, the object must contain a field t containing a numeric
representation of the time, for example, containing the number of seconds, hours, or days since the first
data point.
auto_basis for automatically constructing basis functions.
library(sp)
### Create a synthetic dataset
set.seed(1)
d <- data.frame(lon = runif(n=500,min = -179, max = 179),
lat = runif(n=500,min = -90, max = 90),
z = rnorm(500))
coordinates(d) <- ~lon + lat
slot(d, "proj4string") = CRS("+proj=longlat")
### Now create basis functions on sphere
G <- auto_basis(manifold = sphere(),data=d,
nres = 2,prune=15,
type = "bisquare",
subsamp = 20000)
### Now evaluate basis functions at origin
S <- eval_basis(G,matrix(c(0,0),1,2))
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