# aniso: Fitting anisotropic spatial Gaussian process models In deform: Spatial Deformation and Dimension Expansion Gaussian Processes

 aniso R Documentation

## Fitting anisotropic spatial Gaussian process models

### Description

Function `aniso` fits a conventional 2-dimensional anisotropic Gaussian process, i.e. just with scalings in the x and y coordinates.

### Usage

``````aniso(x, z, n, correlation = FALSE, cosine = FALSE, standardise = "together")
``````

### Arguments

 `x` a 2-column matrix comprising x and y coordinates column-wise, respectively, or a list; see Details for the latter `z` a variance-covariance matrix `n` an integer number of data `correlation` a logical defining whether `z` should be assumed to be a correlation matrix; defaults to `FALSE` `cosine` a logical defining whether the powered exponential covariance function should be multiplied by the cosine of scaled distances, i.e. giving a damped oscillation; defaults to `FALSE` `standardise` a character string that governs whether dimensions are scaled by a common (`"together"`) or dimension-specific factor; defaults to `"together"`

### Details

If `x` is a list, then it wants elements `"x"`, `"z"` and `"n"` as described above.

### Value

An object of class `deform` and then of class `anisotropic`

### References

Sampson, P. D. and Guttorp, P. (1992) Nonparametric Estimation of Nonstationary Spatial Covariance Structure, Journal of the American Statistical Association, 87:417, 108-119, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/01621459.1992.10475181")}'

### Examples

``````
data(solar)
aniso(solar\$x, solar\$z, solar\$n)
# equivalent to aniso(solar)

``````

deform documentation built on Oct. 19, 2023, 9:08 a.m.