rbinomial.mixture {QRMlib} | R Documentation |
random generation from mixed binomial distribution
rbinomial.mixture(n=1000, m=100, model="probitnorm", ...)
n |
sample size |
m |
vector of numbers of coin flips |
model |
name of mixing distribution: "probitnorm", "logitnorm","beta"," |
... |
further parameters of mixing distribution |
see pages 354-355 and pages 375-377 of QRM
vector of numbers of successes
rbeta
,
rprobitnorm
,
rlogitnorm
pi <- 0.04896; #one obligor defaulting pi = .04896 pi2 <- 0.00321; #two obligors defaulting jointly pi2 = .0031265 beta.pars <- cal.beta(pi,pi2); probitnorm.pars <- cal.probitnorm(pi,pi2); n <- 1000; m <- rep(500,n); M.beta <- rbinomial.mixture(n,m,"beta",shape1=beta.pars[1], shape2=beta.pars[2]); M.probitnorm <- rbinomial.mixture(n,m,"probitnorm", mu=probitnorm.pars[1],sigma=probitnorm.pars[2]);