Known-V meta-analytic random effect (deprecated alias): meta_known_V(V = V)

Soft-deprecated alias for meta_V(). Both names desugar identically; new code should use meta_V(V = V). meta_known_V() remains available for backward compatibility.

Usage

meta_known_V(V, type = "exact")

Arguments

V

Known sampling variance or covariance marker. In current exact-additive fits, pass the actual matrix via the top-level known_V = argument to gllvmTMB(). Formula-level V = V names the marker and keeps the syntax aligned with drmTMB::meta_V().

type

Sampling-covariance mode. "exact" is implemented. "proportional" is not implemented and fails clearly in the formula parser rather than being treated as exact.

Value

A formula marker; never evaluated.

See also

meta_V() (canonical name; preferred for new code); meta() (older deprecated short alias); block_V(); gllvmTMB().

Examples

# Deprecated alias of meta_V(); both desugar identically.
# New code should use meta_V(V = V).
set.seed(131)
df <- expand.grid(
  site  = factor(seq_len(50)),
  trait = factor(paste0("t", 1:3))
)
df$value <- rnorm(nrow(df), sd = 0.5)
df$sampling_var <- runif(nrow(df), min = 0.02, max = 0.08)
V <- diag(df$sampling_var)
# \donttest{
fit <- gllvmTMB(
  value ~ 0 + trait + latent(0 + trait | site, d = 1) +
    meta_known_V(V = V),
  data = df, trait = "trait", unit = "site", known_V = V
)
#> ℹ Auto-suppressing `sigma_eps`: `indep(0 + trait | site)` is at the per-row
#>   level, so it already absorbs the observation residual.
#> • Fixed at 0.000528 (~1/1000 of sd(y)) to keep the Gaussian density
#>   well-defined; the row-level residual variance is fully captured by the
#>   per-row diagonal term.
# }