emfrail_dist {frailtyEM} | R Documentation |
Distribution parameters for emfrail
emfrail_dist(dist = "gamma", theta = 2, pvfm = -1/2,
left_truncation = FALSE, basehaz = "breslow")
dist |
One of 'gamma', 'stable' or 'pvf'. |
theta |
A starting value for the 'outer' maximization with respect to the frailty parameter |
pvfm |
Only relevant if |
left_truncation |
Logical. Whether the data set represents left truncated survival times. |
basehaz |
A character string which determines how the baseline hazard is calculated. The default is "breslow", but other possible options are "weibull", "exponential" "gaussian", "logistic", "lognormal" or "loglogistic". |
The theta
argument must be positive. In the case of gamma or PVF, this is the inverse of
the frailty variance, i.e. the larger the theta
is,
the closer the model is to a Cox model. When dist = "pvf"
and pvfm = -0.5
, the inverse Gaussian
distribution is obtained. For the positive stable distribution, the \gamma
parameter of the Laplace transform is
\theta / (1 + \theta)
, with the alpha
parameter fixed to 1.
An object of the type emfrail_dist
, which is mostly used to denote the
supported frailty distributions in a consistent way.
emfrail_dist()
# Compound Poisson distribution:
emfrail_dist(dist = 'pvf', theta = 1.5, pvfm = 0.5)
# Inverse Gaussian distribution:
emfrail_dist(dist = 'pvf')