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3. unstructured – General structure variance models

# unstructured – General structure variance models

###### Description

unstructured: General correlation and covariance models.

###### Usage
```cor(obj, init=NA)
corv(obj, init=NA)
corh(obj, init=NA)
corb(obj, b=1, init=NA)
corbv(obj, init=NA)
corbh(obj, init=NA)
corg(obj, init=NA)
corgv(obj, init=NA)
corgh(obj, init=NA)
diag(obj, init=NA)
us(obj, init=NA)
chol(obj, k=1, init=NA)
ante(obj, k=1, init=NA)
sfa(obj, k=1, init=NA)
facv(obj, k=1, init=NA)
fa(obj, k=1, init=NA)
rr(obj, k=1, init=NA)

```
###### Arguments
 `obj` A factor in `data`. `init` A vector of initial values (correlation 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. `b` Number of (sub-diagonal) bands in banded correlation models. `k` Order of the model (`chol, ante`) or number of factors (`sfa, facv, fa, rr`).
###### Details

The class of general variance models includes the simple, banded and general correlation models (`cor, corb, corg`), the diagonal, unstructured, Cholesky and antedependence variance models (`diag, us, chol, cholc, ante`) and the factor analytic structures (`sfa, facv, fa`).

###### Functions
 `asr_corv:` Simple correlation model, homogeneous variance form. `asr_corh:` Simple correlation model, heterogeneous variance form. `asr_corb:` Banded correlation model with `b`bands. `asr_corbv:` Banded correlation model with `b`bands, homogeneous variance form. `asr_corbh:` Banded correlation model with `b`bands, heterogeneous variance form. `asr_corg:` General correlation model. `asr_corgv:` General correlation model, homogeneous variance form. `asr_corgh: ` General correlation model, heterogeneous variance form. `asr_diag:` Diagonal variance model. `asr_us:` Unstructured variance model. `asr_chol:` Cholesky variance model of order `k`. `asr_ante:` Antedependence variance model of order `k`. `asr_sfa:` Factor analytic model with `k` factors; the variance-covariance matrix is modelled on the correlation scale. `asr_facv:` Factor analytic model with `k` factors; the variance-covariance matrix is modelled on the covariance scale. `asr_fa:` Factor analytic model with `k` factors; sparse formulation where `k` “extra” levels are inserted in the mixed model equations. `asr_rr:` Factor analytic model with `k` factors; reduced rank formulation of `fa()` where the default boundary constraints for the specific variances are set to Fixed.
Updated on June 22, 2021