
Fixed-effect estimates and covariance for a multi-trait fit
Source:R/vcov-coef.R
gllvmTMB_multi-vcov.Rdcoef() returns the fixed-effect point estimates; vcov() returns their
covariance matrix, taken from the fit's TMB sdreport().
Arguments
- object
A fitted multivariate model returned by
gllvmTMB().- ...
Ignored, present for S3 consistency.
Value
coef(): a named numeric vector, one entry per fixed-effect term
(object$X_fix_names).
vcov(): a square numeric matrix with those same names on both margins.
Rows and columns for coefficients held fixed via Xcoef_fixed are NA –
a fixed parameter was not estimated, so it has no sampling covariance.
Point estimates need no standard errors
coef() works on any fit, including one made with
gllvmTMBcontrol(se = FALSE) – point estimates are this package's supported
claim and do not depend on sdreport(). vcov() does depend on it, and
raises the same typed errors confint() does when it is missing
(gllvmTMB_confint_no_sdreport) or non-finite
(gllvmTMB_confint_nonfinite_se), naming standard_errors() as the remedy
in the first case. The conditions are shared deliberately: a caller that
handles one should handle the other.
What this covariance is
The fixed-effect block of the single TMB sdreport() the fit already
carries – a Wald covariance, with exactly the caveats any Wald quantity
from this package carries. It is not a resampled or profiled quantity, and
no interval built from it has certified coverage. vcov() refuses a fit
with non-unit likelihood weights: that fit targets a weighted estimating
objective and has no certified sandwich covariance.
See also
standard_errors() to compute the sdreport() after fitting;
confint() for intervals; summary() for a coefficient table.