moko (version 1.0.3)

mkm: Multi-objective Kriging model

Description

This function creates a multi-objective kriging model. It is based on the km function of the DiceKriging package and creates a structured list of km objects.

Usage

mkm(design, response, modelcontrol = NULL)

Arguments

design

Numeric data.frame of the designs (decision space)

response

Numeric data.frame of the observed responses (objectives and constraints) at each design point.

modelcontrol

An optional list of control parameters passed to the km function. One can control:

objective

(default: 1:ncol(response))

quiet

(default: TRUE)

formula

(default: ~1)

covtype

(default: "matern5_2")

nugget.estim

(default: FALSE)

estim.method

(default: "MLE")

optim.method

(default: "BFGS")

multistart

(default: 1)

gr

(default: TRUE)

iso

(default: FALSE)

scaling

(default: FALSE)

type

(default: 'UK')

se.compute

(default: TRUE)

light.return

(default: TRUE)

bias.correct

(default: FALSE)

checkNames

(default: FALSE)

For more details, one can check km.

Value

S4 An object of class mkm-class

Examples

# NOT RUN {
# ------------------------
# The Nowacki Beam
# ------------------------
n <- 10
d <- 2
doe <- replicate(d,sample(0:n,n))/n
res <- t(apply(doe, 1, nowacki_beam))
model <- mkm(doe, res, modelcontrol = list(objective = 1:2))
# }