rbfST.cv1: RMSPE value result of leave-one-out cross validation for...

In geosptdb: Spatio-Temporal Radial Basis Functions with Distance-Based Methods (Optimization, Prediction and Cross Validation)

RMSPE value result of leave-one-out cross validation for rbfST

Description

It generates the RMSPE value which is given by the spatio-temporal radial basis function with smoothing eta and robustness rho parameters.

Usage

rbfST.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 (covariates or the principal coordinates); suppose the dependent variable has name z_{st}, for a rbfST detrended use z_{st}~1, for a rbfST with trend, suppose z_{st} is linearly dependent on x and y, use the formula z_{st}~x+y (linear trend).
data	SpatialPointsDataFrame: should contain the spatio-temporal dependent variable, independent variables (statics and/or dynamics), spatial coordinates and the time as an integer or numerical variable.
n.neigh	number of nearest observations that should be used for a rbfST prediction, where nearest is defined in terms of the spatio-temporal locations.
func	spatio-temporal radial basis function; model type: "GAU", "EXPON", "TRI", "TPS", "CRS", "ST", "IM" and "M", are currently available

Value

returns the RMSPE value

See Also

rbfST, rbfST.cv, graph.rbfST

Examples

require(minqa)
data(croatiadb)
coordinates(croatiadb) <- ~x+y

## Not run: 
rbf.im <- bobyqa(c(0.5, 0.5), rbfST.cv1, lower=c(1e-05,0), upper=c(2,2), 
              formula=MTEMP~X1+X2+X3+X4+X5+X6+X7+X8+X9+X10, data=croatiadb, n.neigh=25, 
              func="IM", control=list(maxfun=50))         

## End(Not run)

# obtained with the optimal values previously estimated
rbfST.cv1(c(0.847050095690357,0.104157855356128), MTEMP~X1+X2+X3+X4+X5+X6+X7+X8+X9+X10, 
           croatiadb, n.neigh=25, func="IM")

geosptdb documentation built on May 13, 2022, 1:05 a.m.