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Methods for variational (integration = "va") fits

Source: R/va-methods.R
gllvmTMB_va-methods.Rd

Methods for the object returned by gllvmTMB(..., control = gllvmTMBcontrol(integration = "va")).

Usage

# S3 method for class 'gllvmTMB_va'
print(x, digits = 3, ...)

# S3 method for class 'gllvmTMB_va'
summary(object, ...)

# S3 method for class 'summary.gllvmTMB_va'
print(x, digits = 3, ...)

# S3 method for class 'gllvmTMB_va'
nobs(object, ...)

# S3 method for class 'gllvmTMB_va'
logLik(object, ...)

# S3 method for class 'gllvmTMB_va'
confint(object, parm, level = 0.95, ...)

# S3 method for class 'gllvmTMB_va'
vcov(object, ...)

# S3 method for class 'gllvmTMB_va'
coef(object, ...)

# S3 method for class 'gllvmTMB_va'
residuals(object, ...)

# S3 method for class 'gllvmTMB_va'
fitted(object, ...)

# S3 method for class 'gllvmTMB_va'
deviance(object, ...)

# S3 method for class 'gllvmTMB_va'
df.residual(object, ...)

# S3 method for class 'gllvmTMB_va'
weights(object, ...)

# S3 method for class 'gllvmTMB_va'
predict(object, ...)

Arguments

x, object

A fit returned by gllvmTMB() with control = gllvmTMBcontrol(integration = "va").

digits

Decimal digits in the printed output. Default 3.

...

Currently unused.

parm

Fixed-effect coefficient indices or names for confint(). By default all fixed effects are returned.

level

Nominal confidence level for fixed-effect VA-Wald intervals.

Value

print() and print.summary() return their argument invisibly. summary() returns an object of class "summary.gllvmTMB_va". nobs() returns an integer count of unit-by-response cells. vcov() returns the profiled-Schur beta covariance matrix and confint() its nominal Wald intervals; both carry calibrated = FALSE and uncertainty_basis = "VA-Wald profiled Schur information" attributes.

Details

This is an opt-in research route. Its objective is an ELBO – a lower bound on the log-likelihood – not a log-likelihood, and its inverse Hessian is not automatically calibrated frequentist uncertainty. Accordingly logLik(), AIC(), and BIC() remain undefined. vcov() and confint() expose only fixed-effect VA-Wald uncertainty computed from the profiled Schur information matrix. The returned values are explicitly labelled uncalibrated; raw-loading Wald intervals are not available.

The ordination surface is the exception: extract_ordination(), getLV(), getLoadings(), and extract_loadings() all work for a variational fit and return latent scores and loadings as POINT ESTIMATES. getLV(se = TRUE) additionally returns a variational posterior SD – not a standard error – and only when the fit's eval_method resolves to "gh". See the integration argument of gllvmTMB() for the measured accuracy of these point estimates.