Percent damage distribution
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.
Good idea. At this point I do not need to be so precise as to work with a mixture distribution, but I will keep this in mind.
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.
I am trying to model loss severity. One common simplified approach is to sample from e.g. a gamma or lognormal distribution to determine the dollar value of each loss. My problem with this approach is that I have the individual insured amounts, so a $100,000 loss which could result from sampling from a lognormal distribution does not seem reasonable if the insured amount is $25,000, to put an example. That is why I thought of a damage distribution instead. I am not sure what you mean by using a plot analysis or re-sampling the data. I posted back to Ben yesterday and the post was not accepted yet, so it probably does not show in the thread, but there I stated I was going to use a beta distribution, so my problem is solved by now. If you want, we may continue this conversation privately. Many thanks.
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.
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-- 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 ______________________________________________ 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. ----- ~~~~~~~~~~~~~~~~~~~~~~~~~~ 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-tp21170344p21175296.html Sent from the R help mailing list archive at Nabble.com.