survregVB.fit.Calculates the variational Bayes convergence criteria, evidence lower
bound (ELBO), optimized in survregVB.fit.
elbo(
y,
X,
delta,
alpha_0,
omega_0,
mu_0,
v_0,
alpha,
omega,
mu,
Sigma,
expectation_b
)A vector of observed log-transformed survival times.
A design matrix including covariates with first column of ones to represent the intercept.
A binary vector indicating right censoring.
The shape hyperparameter \(\alpha_0\) of the prior distribution of the scale parameter, b.
The shape hyperparameter \(\omega_0\) of the prior distribution of the scale parameter, b.
Hyperparameter \(\mu_0\), a vector of means, of the prior distribution of the vector of coefficients, \(\beta\).
The precision (inverse variance) hyperparameter \(v_0\), of the prior distribution of the vector of coefficients, \(\beta\).
The shape parameter \(\alpha^*\) of \(q^*(b)\).
The scale parameter \(\omega^*\) of \(q^*(b)\).
Parameter \(\mu^*\) of \(q^*(\beta)\), a vector of means.
Parameter \(\Sigma^*\) of \(q^*(\beta)\), a covariance matrix.
The expected value of b.
survregVB.fit