emfrail_dist: Distribution parameters for emfrail
In frailtyEM: Fitting Frailty Models with the EM Algorithm

Description Usage Arguments Details Value See Also Examples

Distribution parameters for emfrail

1 2	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 θ. Must be >0.
`pvfm`	Only relevant if `dist = 'pvf'` is used. It determines which PVF distribution should be used. Must be larger than -1 and not equal to 0.
`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 γ parameter of the Laplace transform is θ / (1 + θ), 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, emfrail_control

emfrail_dist()
# Compound Poisson distribution:
emfrail_dist(dist = 'pvf', theta = 1.5, pvfm = 0.5)
# Inverse Gaussian distribution:
emfrail_dist(dist = 'pvf')

Loading required package: survival
$dist
[1] "gamma"

$theta
[1] 2

$pvfm
[1] -0.5

$left_truncation
[1] FALSE

attr(,"class")
[1] "emfrail_dist"
$dist
[1] "pvf"

$theta
[1] 1.5

$pvfm
[1] 0.5

$left_truncation
[1] FALSE

attr(,"class")
[1] "emfrail_dist"
$dist
[1] "pvf"

$theta
[1] 2

$pvfm
[1] -0.5

$left_truncation
[1] FALSE

attr(,"class")
[1] "emfrail_dist"