predict.BPST: Make predictions from a fitted BPST object.

In FIRST-Data-Lab/BPST: Bivariate Spline over Triangulation

Make predictions from a fitted BPST object.

Description

This function is used to make predictions of a fitted BPST object.

Usage

## S3 method for class 'BPST'
predict(mfit, Zpred = NULL)

Arguments

mfit	Fitted “BPST" object.
Zpred	The cooridinates for prediction – default is the observed coordinates, Z.

Details

This R program is modified based on the Matlab program written by Ming-Jun Lai from the University of Georgia and Li Wang from the Iowa State University.

Value

A vector of predicted values is returned.

Examples

# Triangulation
# Option 1;
# data(V1); data(Tr1); d=5; r=1; V=V1; Tr=Tr1;
# Option 2
data(V2); data(Tr2); d=5; r=1; V=V2; Tr=Tr2;
d=5; r=1;
# Grid Points
n1.grid=101; n2.grid=101; n.grid=n1.grid*n2.grid;
u.grid=seq(0,1,length.out=n1.grid)
v.grid=seq(0,1,length.out=n2.grid)
uu.grid=rep(u.grid,each=n2.grid)
vv.grid=rep(v.grid,times=n1.grid)
Z.grid=as.matrix(cbind(uu.grid,vv.grid))
func=1; sigma=0.1;
gridpoints=data.BPST(Z.grid,V,Tr,func,sigma,2019)
Y.grid=gridpoints$Y; mu.grid=gridpoints$mu;
ind=gridpoints$ind; ind.grid=(1:n.grid)[ind==1];
# Simulation parameters
n=2000;
ind.sam=sort(sample(ind.grid,n))
Y=as.matrix(gridpoints$Y[ind.sam]); Z=as.matrix(gridpoints$Z[ind.sam,]);
mfit=fit.BPST(Y,Z,V,Tr,d,r,lambda=10^seq(-6,6,by=0.5))
rmse=sqrt(mean((Y-mfit$Yhat)^2,na.rm=TRUE))
mpred=predict(mfit,Z.grid)
rmspe=sqrt(mean((Y.grid-mpred$Ypred)^2,na.rm=TRUE))
cat("rmse =",rmse,"and rmspe =",rmspe,"\n")

FIRST-Data-Lab/BPST documentation built on Sept. 18, 2023, 7:31 a.m.