Produces a summary of a fitted Variational Bayes Parametric Survival Regression Model for a Log-Logistic AFT Model
# S3 method for survregVB
summary(object, ci = 0.95, ...)An object of class summary.survregVB with components:
ELBO: The final value of the Evidence Lower Bound (ELBO)
at the last iteration.
alpha: The shape parameter \(\alpha^*\) of \(q^*(b)\).
omega: The scale parameter \(\omega^*\) of \(q^*(b)\).
mu: Parameter \(\mu^*\) of \(q^*(\beta)\), a vector
of means.
Sigma: Parameter \(\Sigma^*\) of \(q^*(\beta)\), a
covariance matrix.
na.action: A missing-data filter function, applied to the
model.frame, after any subset argument has been used.
iterations: The number of iterations performed by the VB
algorithm: before converging or reaching max_iteration.
n: The number of observations.
call: The function call used to invoke the survregVB
method.
not_converged: A boolean indicating if the algorithm
converged.
TRUE: If the algorithm did not converge prior to
achieving max_iteration.
NULL: If the algorithm converged successfully.
estimates: A matrix with one row for each regression coefficient,
and one row for the scale parameter. The columns contain:
Value: The estimated value based on the posterior
distribution mean.
Lower CI: The lower bound of the credible interval.
Upper CI: The upper bound of the credible interval.
If called with shared frailty, the object also contains components:
lambda: The shape parameter \(\lambda^*\) of
\(q^*(\sigma^2_\gamma)\).
eta: The scale parameter \(\eta^*\) of
\(q^*(\sigma^2_\gamma)\).
tau: Parameter \(\tau^*_i\) of \(q^*(\gamma_i)\), a
vector of means.
sigma: Parameter \(\sigma^{2*}_i\) of \(q^*(\gamma_i)\),
a vector of variance.
The estimates component will contain an additional row for the
frailty, the estimated variance based on the posterior mean for the
random intercepts.
The result of a survregVB fit.
The significance level for the credible intervals. (Default:0.95).
For future arguments.
survregVB