Therneau, Terry M., Ph.D. <therneau <at> mayo.edu> writes:

>

>

> On 12/26/2014 05:00 AM, r-help-request <at> r-project.org wrote:

> > i want to analyse survival data using typeI HALF LOGISTIC

> > DISTRIBUTION.how can i go about it?it installed one on R in the

> > survival package didn't include the distribution...or i need a code to

> > use maximum likelihood to estimate the parameter in survival

> > analysis.a typical example of distribution other than that installed

> > in R will help.thanks

> >

> I am the author of the survival package, and had never heard of the

> "type I half-logistic" before. New distributions can be added to

> survreg() if they can be represented as location-scale families; I

> don't think that your distribution can be written in that way. Look

> at "survival" under the "Task Views" tab (upper left corner) of the

> cran.org web page

I don't know about 'type I' but based on

http://en.wikipedia.org/wiki/Half-logistic_distribution you could try

dhalflogist <- function(x,s,log=FALSE) {

r <- log(2)-log(s)-x/s-2*log(1+exp(-x/s))

if (log) r else exp(r)

}

phalflogist <- function(q,s) { (1-exp(-q/s))/(1+exp(-(q/s))) }

rhalflogist <- function(n,s) { abs(rlogis(n,scale=s)) }

set.seed(101)

rr <- rhalflogist(10000,2)

hist(rr,freq=FALSE,breaks=80,col="gray")

curve(dhalflogist(x,2),add=TRUE,col=2,lwd=2)

d <- data.frame(rr)

library("bbmle")

m1 <- mle2(rr~dhalflogist(s=exp(logs)),start=list(logs=0),data=d)

If you want to fit multiple groups etc., see the 'parameters'

argument of ?mle2

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