checkPredict {DiceOptim} | R Documentation |

## Prevention of numerical instability for a new observation

### Description

Check that the new point is not too close to already known observations to avoid numerical issues. Closeness can be estimated with several distances.

### Usage

```
checkPredict(x, model, threshold = 1e-04, distance = "covdist", type = "UK")
```

### Arguments

`x` |
a vector representing the input to check, |

`model` |
list of objects of class |

`threshold` |
optional value for the minimal distance to an existing observation, default to |

`distance` |
selection of the distance between new observations, between " |

`type` |
" |

### Details

If the distance between `x`

and the closest observations in `model`

is below
`threshold`

, `x`

should not be evaluated to avoid numerical instabilities.
The distance can simply be the Euclidean distance or the canonical distance associated with the kriging covariance k:

`d(x,y) = \sqrt{k(x,x) - 2k(x,y) + k(y,y)}.`

The last solution is the ratio between the prediction variance at `x`

and the variance of the process.

### Value

`TRUE`

if the point should not be tested.

### Author(s)

Mickael Binois

*DiceOptim*version 2.1.1 Index]