rbf.cv1 {geospt} | R Documentation |
Generates a RMSPE value, result of cross validation leave-one-out
Description
Generate the RMSPE value, which is given by the radial basis function with smoothing parameter eta and robustness parameter rho.
Usage
rbf.cv1(param, formula, data, n.neigh, func)
Arguments
param |
vector starting points (eta and rho respectively) for searching the RMSPE optimum. |
formula |
formula that defines the dependent variable as a linear model of independent variables; suppose the dependent variable has name z, for a rbf detrended use z~1, for a rbf with trend, suppose z is linearly dependent on x and y, use the formula z~x+y (linear trend). |
data |
SpatialPointsDataFrame: should contain the dependent variable, independent variables, and coordinates. |
n.neigh |
number of nearest observations that should be used for a rbf prediction, where nearest is defined in terms of the spatial locations |
func |
radial basis function model type, e.g. "GAU", "EXPON", "TRI", "TPS", "CRS", "ST", "IM" and "M", are currently available |
Value
returns the RMSPE value
See Also
Examples
## Not run:
data(preci)
coordinates(preci) <- ~x+y
bobyqa(c(0.5, 0.5), rbf.cv1, lower=c(1e-05,0), upper=c(2,2), formula=prec~x+y, data=preci,
n.neigh=9, func="TRI")
# obtained with the optimal values previously estimated
rbf.cv1(c(0.2126191,0.1454171), prec~x+y, preci, n.neigh=9, func="TRI")
## End(Not run)