# leaveOneOutFun

##### Leave-one-out least square criterion of a km object

Returns the mean of the squared leave-one-out errors, computed with Dubrule's formula.

##### Usage

`leaveOneOutFun(param, model, envir = NULL)`

##### Arguments

- param
a vector containing the optimization variables.

- model
an object of class

`km`

.- envir
an optional environment specifying where to assign intermediate values for future gradient calculations. Default is NULL.

##### Value

The mean of the squared leave-one-out errors.

##### Note

At this stage, only the standard case has been implemented: no nugget effect, no observation noise.

##### References

F. Bachoc (2013), Cross Validation and Maximum Likelihood estimations of hyper-parameters of Gaussian processes with model misspecification. *Computational Statistics and Data Analysis*, **66**, 55-69. http://www.lpma.math.upmc.fr/pageperso/bachoc/publications.html

O. Dubrule (1983), Cross validation of Kriging in a unique neighborhood. *Mathematical Geology*, **15**, 687-699.

##### See Also

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