| survreg.distributions {survival} | R Documentation |
List of distributions for accelerated failure models. These are location-scale families for some transformation of time. The entry describes the cdf F and density f of a canonical member of the family.
survreg.distributions
There are three basic formats; only the first two are used in the built-in distributions
| name: | name of distribution |
| variance: | Variance |
| init(x,weights,...): | Function returning an initial |
| mean and | variance |
| deviance(y,scale,parms): | Function returning the deviance |
| density(x,parms): | Function returning F, |
| 1-F,f,f'/f,f''/f | |
| quantile(p,parms): | Quantile function |
| scale: | Optional fixed value for scale parameter |
and for transformations of the time variable
| name: | name of distribution |
| dist: | name of transformed distribution |
| trans: | transformation (eg log) |
| dtrans: | derivative of transformation |
| itrans: | inverse of transformation |
| scale: | Optional fixed value for scale parameter |
For transformations of user-defined families use
| name: | name of distribution |
| dist: | transformed distribution in first format |
| trans: | transformation (eg log) |
| dtrans: | derivative of transformation |
| itrans: | inverse of transformation |
| scale: | Optional fixed value for scale parameter |
There are four basic distributions:extreme, gaussian,
logistic and t. The last three
are parametrised in the same way as the distributions already present in
R. The extreme value cdf is
F=1-e^{-e^t}.
When the logarithm of survival time has one of the first three distributions
we obtain respectively weibull, lognormal, and
loglogistic. The Weibull distribution is not parameterised the
same way as in rweibull.
The other predefined distributions are defined in terms of these. The
exponential and rayleigh distributions are Weibull
distributions with fixed scale of 1 and 0.5 respectively, and
loggaussian is a synonym for lognormal.
Parts of the built-in distributions are hardcoded in C, so the elements
of survreg.distributions in the first format above must not be
changed and new ones must not be added. The examples show how to
specify user-defined distributions to survreg.
## not a good fit, but a useful example survreg(Surv(futime,fustat)~ecog.ps+rx,data=ovarian,dist='extreme') ## my.extreme<-survreg.distributions$extreme my.extreme$name<-"Xtreme" survreg(Surv(futime,fustat)~ecog.ps+rx,data=ovarian,dist=my.extreme) ## time transformation survreg(Surv(futime,fustat)~ecog.ps+rx,data=ovarian,dist='weibull',scale=1) my.weibull<-survreg.distributions$weibull my.weibull$dist<-my.extreme survreg(Surv(futime,fustat)~ecog.ps+rx,data=ovarian,dist=my.weibull,scale=1) ## change the transformation to work in years ## intercept changes by log(365), other coefficients stay the same my.weibull$trans<-function(y) log(y/365) my.weibull$itrans<-function(y) exp(365*y) survreg(Surv(futime,fustat)~ecog.ps+rx,data=ovarian,dist=my.weibull,scale=1) ## Weibull parametrisation y<-rweibull(1000, shape=2, scale=5) survreg(Surv(y)~1, dist="weibull") ## survreg reports scale=1/2, intercept=log(5)