Here are some datasets that can be used for the first homework, on extremes
- Daily rainfall accumulation, in South-West England [csv]
- Business Interruption claims, in France [xls]
- Fire insurance claims, in France [csv]
- Hurricane losses, in the United States [csv]
- Tornado losses, in the United States [csv]
- Hail losses, in the United States [csv]
- Flooding losses, in the United States [csv]
- Sea level, in Venice, Italy [csv]
- River level of the Seine, in Pommeuse, France [txt]
- Daily precipitation, in some city, France, 0.1 mm [txt]
- Daily (maximum) temperature, in some city, France 0.1°C [txt]
- Large medical claims [zip, zip, zip]
Note that to import some datasets, it might be necessary to skip some lines. The standard code to import a dataset it the following,
data/RR_SOUID104968.txt", skip=20,nrows=43460,header=TRUE,sep=",") date=as.Date(as.character(base$DATE),"%Y%m%d") rain=base$RR
The last three datasets are from the Medical Large Claims Experience Study (http://www.soa.org/). Datasets are extremely large (more than 200Mo), and once data are extracted, they can be imported in R using
Note that information about the variates of the dataset can be found on the website.
If some students want to work on some specific data, please send me first a copy of the series.
For this first homework, I expect students to write a short report (5 pages maximum) containing an estimation of a 99.9% quantile (per claim or per day for daily time series), and the amount associated to a 10-year return period.
I will post some R functions on the blog soon.
Published on Sunday, January 22 2012 by arthur charpentier