# kmData

##### Fit and/or create kriging models

`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`

.

##### Usage

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

##### Arguments

- 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`

.

##### Value

An object of class `km`

(see `km-class`

).

##### See Also

##### Examples

```
# 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"))
# }
```

*Documentation reproduced from package DiceKriging, version 1.5.6, License: GPL-2 | GPL-3*