R: Metric-based variance models in two dimensions

metric-2D_vs {asreml} | R Documentation

## Metric-based variance models in two dimensions

### Description

Metric-based variance structures in two dimensions. Includes two-dimensional isotropic exponential, gaussian, euclidean, linear variance, spherical and circular power models (`iexp`, `igau`, `ieuc`, `ilv`, `sph`, `cir`), anisotropic exponential and gaussian models (`aexp`, `agau`) and the Matern class (`mtrn`).

### Usage

    iexp(x, y, init = NA)

    iexpv(x, y, init = NA)

    iexph(x, y, init = NA)

    aexp(x, y, init = NA)

    aexpv(x, y, init = NA)

    aexph(x, y, init = NA)

    igau(x, y, init = NA)

    igauv(x, y, init = NA)

    igauh(x, y, init = NA)

    agau(x, y, init = NA)

    agauv(x, y, init = NA)

    agauh(x, y, init = NA)

    ieuc(x, y, init = NA)

    ieucv(x, y, init = NA)

    ieuch(x, y, init = NA)

    ilv(x, y, init = NA)

    ilvv(x, y, init = NA)

    ilvh(x, y, init = NA)

    sph(x, y, init = NA)

    sphv(x, y, init = NA)

    sphh(x, y, init = NA)

    cir(x, y, init = NA)

    cirv(x, y, init = NA)

    cirh(x, y, init = NA)

### Arguments

`x` | An object in `data` containing the x coordinates.
`y` | An object in `data` containing the y coordinates.
`init` | An optional vector of initial values (power parameters followed by variance parameters) with an optional `names` attribute from the set {`P`, `U`, `F`} specifying the boundary constraint as positive, unconstrained or fixed, respectively.

### Functions

- `asr_iexp()`: Exponential (or power) model; correlation form.

- `asr_iexpv()`: Exponential (or power) model; homogeneous variance form.

- `asr_iexph()`: Exponential (or power) model; heterogeneous variance form.

- `asr_aexp()`: Anisotropic exponential variance model; correlation form.

- `asr_aexpv()`: Anisotropic exponential variance model; homogeneous variance form.

- `asr_aexph()`: Anisotropic exponential variance model; heterogeneous variance form.

- `asr_igau()`: Isotropic Gaussian variance model; correlation form.

- `asr_igauv()`: Isotropic Gaussian variance model; homogeneous variance form.

- `asr_igauh()`: Isotropic Gaussian variance model; heterogeneous variance form.

- `asr_agau()`: Anisotropic Gaussian variance model; correlation form.

- `asr_agauv()`: Anisotropic Gaussian variance model; homogeneous variance form.

- `asr_agauh()`: Anisotropic Gaussian variance model; heterogeneous variance form.

- `asr_ieuc()`: Isotropic Euclidean variance model; correlation form.

- `asr_ieucv()`: Isotropic Euclidean variance model; homogeneous variance form.

- `asr_ieuch()`: Isotropic Euclidean variance model; heterogeneous variance form.

- `asr_ilv()`: Isotropic linear variance model; correlation form.

- `asr_ilvv()`: Isotropic linear variance model; homogeneous variance form.

- `asr_ilvh()`: Isotropic linear variance model; heterogeneous variance form.

- `asr_sph()`: Spherical variance model; correlation form.

- `asr_sphv()`: Spherical variance model; homogeneous variance form.

- `asr_sphh()`: Spherical variance model; heterogeneous variance form.

- `asr_cir()`: Circular variance model; correlation form.

- `asr_cirv()`: Circular variance model; homogeneous variance form.

- `asr_cirh()`: Circular variance model; heterogeneous variance form.

[Package asreml version 4.2.0.480 Index]