Percent damage distribution
Not an R question as yet ..... In my limited experience (we have some insurance projets), 100% can occur, but otherwise a beta distbribution may suit, which suggests a mixture distribution. But start with an empirical examination (histogram, ecdf, density plot) of the distribution, since it may reveal other features. The next question is 'why model'? For such a simple problem (a univariate distribution) a plot may be a sufficent analysis, and for e.g. simulation you could just re-sample the data.
On Thu, 25 Dec 2008, diegol wrote:
R version: 2.7.0 Running on: WinXP I am trying to model damage from fire losses (given that the loss occurred). Since I have the individual insured amounts, rather than sampling dollar damage from a continuous distribution ranging from 0 to infinity, I want to sample from a percent damage distribution from 0-100%. One obvious solution is to use runif(n, min=0, max=1), but this does not seem to be a good idea, since I would not expect damage to be uniform. I have not seen such a distribution in actuarial applications, and rather than inventing one from scratch I thought I'd ask you if you know one, maybe from other disciplines, readily available in R. Thank you in advance. ----- ~~~~~~~~~~~~~~~~~~~~~~~~~~ Diego Mazzeo Actuarial Science Student Facultad de Ciencias Econ?micas Universidad de Buenos Aires Buenos Aires, Argentina -- View this message in context: http://www.nabble.com/Percent-damage-distribution-tp21170344p21170344.html Sent from the R help mailing list archive at Nabble.com.
______________________________________________ R-help at r-project.org 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.
Brian D. Ripley, ripley at stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595