idwST.cv1: Generate a RMSPE value, result of leave-one-out cross...

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

Generate a RMSPE value, result of leave-one-out cross validation

Description

Generate the RMSPE value which is given by the radial basis function spatio-temporal with number of nearest observationsn.neigh associated to time factor C and optimal smoothing parameter factor.p.

Usage

idwST.cv1(param, formula, data, n.neigh, progress)

Arguments

param	vector starting points (C and factor.p respectively) for searching the RMSPE optimum.
formula	formula that defines a detrended linear model, use z_{st}~1.
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 rbf.st prediction where nearest is defined in terms of the spatio-temporal locations
progress	whether a progress bar shall be printed for spatio-temporal inverse-distance weighted function; default=FALSE

Value

returns the RMSPE value

See Also

idwST, idwST.cv, idwST.tcv

Examples

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

## Not run: 
idwST.opt <- bobyqa(c(1, 2), idwST.cv1, lower=c(0,0.1), upper=c(2,4), formula=MTEMP~1, 
                    data=croatiadb[,1:2], n.neigh=10, progres=F, control=list(maxfun=50))         

# obtained with optimal values previously estimated (33 iterations)
idwST.cv1(c(1.00538675066736,1.95853920335545), MTEMP~1, data=croatiadb[,1:2], n.neigh=10, 
          progress=T)

## End(Not run)

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