cokm.predict {ARCokrig} R Documentation

## Prediction at new inputs in the autoregressive cokriging model

### Description

This function makes prediction in autogressive cokriging models. If a nested design is used, the predictive mean and predictive variance are computed exactly; otherwise, Monte Carlo simulation from the predictive distribution is used to approximate the predictive mean and predictive variance.

### Usage

cokm.predict(obj, input.new)


### Arguments

 obj a cokm object construted via the function cokm in this package input.new a matrix including new inputs for making prediction

### Author(s)

Pulong Ma <mpulong@gmail.com>

cokm, cokm.fit, cokm.condsim, ARCokrig

### Examples

Funcc = function(x){
return(0.5*(6*x-2)^2*sin(12*x-4)+10*(x-0.5)-5)
}

Funcf = function(x){
z1 = Funcc(x)
z2 = 2*z1-20*x+20 + sin(10*cos(5*x))
return(z2)
}

#####################################################################
###### Nested design
#####################################################################
Dc <- seq(-1,1,0.1)
indDf <- c(1, 3, 6, 8, 10, 13, 17, 21)
zc <- Funcc(Dc)
Df <- Dc[indDf]
zf <- Funcf(Df)

input.new = as.matrix(seq(-1,1,length.out=200))

## create the cokm object
prior = list(name="Reference")
obj = cokm(formula=list(~1,~1+x1), output=list(c(zc), c(zf)),
input=list(as.matrix(Dc), as.matrix(Df)),
prior=prior, cov.model="matern_5_2")

## update model parameters in the cokm object

obj = cokm.fit(obj)

cokrige = cokm.predict(obj, input.new)



[Package ARCokrig version 0.1.2 Index]