| spdata {QRMlib} | R Documentation |
The spdata timeSeries dataset has 100 rows and 3 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:
| 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
#Must attach MASS and nlme libraries to run mixed effect regression model
library(MASS);
library(nlme);
#Load timeSeries:
data(spdata); #timeSeries
ratingval <- spdata@recordIDs$rating;
yearval <- as.numeric(spdata@recordIDs$DATE);
#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 + ratingval,
random = ~1| yearval, family=binomial(probit), data=spdata);
results;
summary(results);
summary(results)$tTable[,1];
detach("package:nlme");
detach("package:MASS");