R: Fit and/or create kriging models

kmData {DiceKriging} | R Documentation

## Fit and/or create kriging models

### Description

`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`).

### Author(s)

O. Roustant

### See Also

`km`

### Examples

    # 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"))

[Package DiceKriging version 1.6.0 Index]