Computes the (generalized) Akaike An Information Criterion for a fitted parametric model.
Usage
# S3 method for class 'survstan'
extractAIC(fit, scale, k = 2, ...)Arguments
- fit
a fitted model of the class survstan
- scale
optional numeric specifying the scale parameter of the model. Currently only used in the "lm" method, where scale specifies the estimate of the error variance, and scale = 0 indicates that it is to be estimated by maximum likelihood.
- k
numeric specifying the ‘weight’ of the equivalent degrees of freedom part in the AIC formula.
- ...
further arguments passed to or from other methods.
Examples
# \donttest{
library(survstan)
fit1 <- aftreg(Surv(futime, fustat) ~ 1, data = ovarian, baseline = "weibull", init = 0)
fit2 <- aftreg(Surv(futime, fustat) ~ rx, data = ovarian, baseline = "weibull", init = 0)
fit3 <- aftreg(Surv(futime, fustat) ~ ecog.ps + rx, data = ovarian, baseline = "weibull", init = 0)
extractAIC(fit1)
#> [1] 2.00000 29.21194
extractAIC(fit2)
#> [1] 3.0000 200.7283
extractAIC(fit3)
#> [1] 4.000 202.169
# }