Have a look at the survSplit function in the survival package.  It looks to
me as though you could use survreg with the "weibull" option to achieve what
you want.  Otherwise, you'll have to rewrite the likelihood in terms of both
start and end times.

On 14/09/06, Martin Wagner <martin.wagner@ilr.tu-berlin.de> wrote:

> Hello,

I am trying to model an intensity function with time-varying covariates.
Before, I have successfully defined a log likelihood function for a
Power-Law Process (lambda(t)=alpha*beta*t^(beta-1))  with two paramters
and no covariates for a repairable systems with failure times (t).
This function was maximized with R optim. No problem!

But now I want to include a covariate indicating a time-varying value at
each failure time t. For constant covariates, the procedure is feasible :


leads to following log likelihood funciton:


here zi are the covariates which are constant for each unit i under
observation. tij are the failure time for failure j of unit i.

Do you know how to formulate a log likelihood function for covariates
which vary for each tj of each unit i ?

Thank you very much
Best regards

Martin Wagner
Berlin University of Technology


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-- 
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David Barron
Said Business School
University of Oxford
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David Barron
Said Business School
University of Oxford
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Oxford OX1 1HP

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