Hi Folks, I've just come across a kind of problem which leads me to wonder how to approach it in R.
Basically, each a set of items is subjected to a series of "impacts" until it eventually "fails". The "force" of each impact would depend on covariates X,Y say; but as a result of preceding impacts an item would be expected to have a "cumulative frailty" such that the probability of failure due to a particular impact would possibly increase according to the series of impacts already survived. Without the "cumulative frailty" one could envisage something like a logistic model for the probabiliy of failure at each impact, leading to a kind of generalised "exponential distribution" -- that is, the likelihood for each item would be of the form (1-P[1])*(1-P[2])*...*(1-P[n-1])*P[n] where P[i] could have a logistic model in terms of the values of X[i] and Y[i], and n is the index of the impact at which failure occurred. That is then a solvable problem. Even so, I'm not (so far) finding in the R resources the appropriate analogue of glm for this kind of model. I dare say a prolonged trawl through the various "survival" resources might lead to something applicable, but ... And then there's the cumulative frailty ... ! Suggestions welcome! With thanks, Ted. -------------------------------------------------------------------- E-Mail: (Ted Harding) <[EMAIL PROTECTED]> Fax-to-email: +44 (0)870 094 0861 Date: 22-Sep-06 Time: 20:25:12 ------------------------------ XFMail ------------------------------ ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
