survregVB.object | R Documentation |
This class of objects is returned by the survregVB function to represent
a fitted parametric log-logistic accelerated failure time (AFT) survival
model. Objects of this class have methods for the functions print
and summary
.
For approximate posterior distributions:
q^*(\beta)
, a N_p(\mu^*,\Sigma^*)
density function, and
q^*(b)
, an \text{Inverse-Gamma}(\alpha^*,\omega^*)
density function,
the components of this class are:
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.
If survregVB
was called with shared frailty (with the cluster
argument), for approximate posterior distributions:
q^*(\sigma^2_\gamma)
, an \text{Inverse-Gamma}(\lambda^*,\eta^*)
density function,
q^*(\gamma_i)
, a N(\tau^*_i,\sigma^{2*}_i)
density function,
for i=1,...,K
clusters, and
the additional components are present:
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.
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