error_struct: Error Structures in mvord
In mvord: Multivariate Ordinal Regression Models

Different error.structures are available in mvord:

general correlation structure (default) cor_general(~ 1),
general covariance structure cov_general(~ 1),
factor dependent correlation structure cor_general(~ f),
factor dependent covariance structure cov_general(~ f),
equicorrelation structure cor_equi(~ 1),
covariate dependent equicorrelation structure cor_equi(~ S),
AR(1) correlation structure cor_ar1(~ 1), or
covariate dependent AR(1) correlation structure cor_ar1(~ S).

For more details see vignette.

cov_general(formula = ~1, value = numeric(0), fixed = FALSE)

cor_general(formula = ~1, value = numeric(0), fixed = FALSE)

cor_ar1(formula = ~1, value = numeric(0), fixed = FALSE)

cor_equi(formula = ~1, value = numeric(0), fixed = FALSE)

`formula`	`formula` object
`value`	specifies values of the correlation (and variance) parameters. For `cor_equi()` and `cor_ar1()` it can be either a vector of correlations (in (-1,1)) of length one (same correlation for all subjects) or a vector of length equal to the number of subjects. For `cor_general()`, it can be either a vector of the lower triangular correlation matrix elements (same structure for all subjects) or a matrix with number of rows equal to the number of subjects. For `cov_general()`, it can be either a vector of the lower triangular covariance matrix elements (including the diagonal) (same structure for all subjects) or a matrix with number of rows equal to the number of subjects. Default is `value = numeric(0)` object. In this case the correlation parameters are initialized with zero (and variance parameters with 1 for `cov_general`)
`fixed`	logical specifying whether the parameters of the error structure should not be optimized in the procedure, but will be fixed to the values specified in the argument `value`. Defaults to `fixed = FALSE`.