`kmData`

is equivalent to `km`

, except for the interface with the data. In `kmData`

, the user must supply both the design and the response within a single data.frame `data`

. To supply them separately, use `km`

.

`kmData(formula, data, inputnames = NULL, ...)`

formula

an object of class "formula" specifying the linear trend of the kriging model (see `lm`

). At this stage, transformations of the response are not taken into account.

data

a data.frame containing both the design (input variables) and the response (1-dimensional output given by the objective function at the design points).

inputnames

an optional vector of character containing the names of variables in `data`

to be considered as input variables. By default, all variables but the response are input variables.

…

other arguments for creating or fitting Kriging models, to be taken among the arguments of `km`

function apart from `design`

and `response`

.

An object of class `km`

(see `km-class`

).

# NOT RUN { # a 16-points factorial design, and the corresponding response d <- 2; n <- 16 design.fact <- expand.grid(x1=seq(0,1,length=4), x2=seq(0,1,length=4)) y <- apply(design.fact, 1, branin) data <- cbind(design.fact, y=y) # kriging model 1 : matern5_2 covariance structure, no trend, no nugget effect m1 <- kmData(y~1, data=data) # this is equivalent to: m1 <- km(design=design.fact, response=y) # now, add a second response to data: data2 <- cbind(data, y2=-y) # the previous model is now obtained with: m1_2 <- kmData(y~1, data=data2, inputnames=c("x1", "x2")) # }