spdata.df {QRMlib} | R Documentation |
The spdata.df
data.frame has 100 rows and 4 columns.
It contains default data for A, BBB, BB, B and C-rated companies for the years 1981 to 2000
data(spdata)
a matrix containing 100 rows and 4 columns.
The colums are:
year | year of default |
rating | rating category (A, BBB, BB, B, CCC) |
firms | number of companies in rating category |
number of defaults | number of companies defaulting in category |
The rows are the years from 1981-2000
documentation by Scott Ulman for R-language distribution
Standard and Poors Credit Monitor
#Easier to use data.frame than timeSeries for this set data(spdata.df); #the data being used is spdata.df which has 100 rows and 4 columns: #'year', 'rating', 'firms', defaults' #Must attach MASS and nlme libraries to run mixed effect regression model library(MASS); library(nlme); #Use R- library MASS to get glmmPQL which runs a mixed-effects model. #It will measure random effects and fixed effects. #'year' -'ratings' determine the unique results(20 years 1981-2000 with 5 obligor #class ratings each year) results <- glmmPQL(cbind(defaults,firms-defaults) ~ -1 + rating, random = ~1| year, family=binomial(probit), data=spdata.df); results; summary(results); summary(results)$tTable[,1]; rm(spdata.df); detach("package:nlme"); detach("package:MASS");