# gauss

##### Gaussian Covariance Model

`gauss`

is a stationary isotropic covariance model.
The corresponding covariance function only depends on the distance
\(r \ge 0\) between two points and is given by
$$C(r) = e^{-r^2}$$

##### Usage

`gauss(x, derivative=0)`

##### Arguments

- x
numerical vector; for negative values the modulus is used

- derivative
value in

`0:4`

.

##### Value

If `derivative=0`

, the function value is
returned, otherwise the `derivative`

th derivative.

A vector of `length(x)`

is returned; `nu`

is recycled;
`scaling`

is recycled if numerical.

##### References

Gelfand, A. E., Diggle, P., Fuentes, M. and Guttorp,
P. (eds.) (2010) *Handbook of Spatial Statistics.*
Boca Raton: Chapman & Hall/CRL.

Stein, M. L. (1999) *Interpolation of Spatial Data.* New York: Springer-Verlag

##### See Also

For more details see `RMgauss`

.

##### Examples

```
# NOT RUN {
x <- 3
confirm(gauss(x), exp(-x^2))
# }
```

*Documentation reproduced from package RandomFieldsUtils, version 0.5.3, License: GPL (>= 3)*

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