Extract residual correlation structure for nlme, brms, and glmmTMB models.
extract_cor_structure(model, digits = 3, ...)
# S3 method for lme
extract_cor_structure(model, digits = 3, ...)
# S3 method for glmmTMB
extract_cor_structure(
model,
digits = 3,
...,
component = "cond",
which_cor,
full_matrix = FALSE
)
# S3 method for brmsfit
extract_cor_structure(model, digits = 3, ..., ci_level = 0.95)
An appropriate mixed model.
Rounding. Default is 3.
Other arguments specific to the method. Unused at present.
For glmmTMB objects, which of the three components 'cond', 'zi' or 'disp' to select. Default is 'cond'.
Required for glmmTMB. Which correlation parameter to extract. Must be one of 'ar1', 'ou', 'cs', 'toep', 'diag','us', 'mat', 'gau', 'exp'.
For glmmTMB correlation, return the full residual
covariance/correlation matrix (TRUE
), or simplified output where possible
(FALSE
). Default is FALSE
. See details.
For brms objects, confidence level < 1, typically above 0.90. A value of 0 will not report it. Default is .95.
For nlme and glmmTMB models, a data frame of the estimates. For brms, the parameters and related uncertainty, similar to extract_fixed_effects.
This function applies to models with residual correlation, i.e. that
contain something like corAR1(form = ~time)
for nlme, or brms models with
an something like ar()
in the formula. This functions extracts the
associated parameters (e.g. Phi
in nlme, ar[1]
in brms, etc.)
For glmmTMB objects, rather than the full matrix, simplified output is
provided by default. For ar1
, ou
, cs
, a single value; for toep
(toeplitz) a single row/column; for diag
structures just the diagonal. In
addition, for diag
the residual variance is added to the estimates.
For more detail, see this 'braindump' from Ben Bolker, and the glmmTMB vignette.
Most types of spatial models should work as well.
Other extract:
extract_fixed_effects()
,
extract_het_var()
,
extract_model_data()
,
extract_random_coefs()
,
extract_random_effects()
,
extract_vc()