mbbefd (version 0.7)

mbbefd-distr: The MBBEFD distribution (two parametrizations)

Description

These functions perform probabilistic analysis as well as random sampling on the MBBEFD distribution.

Usage

rmbbefd(n, a, b, g)
dmbbefd(x, a, b, g)
qmbbefd(p, a, b, g)
pmbbefd(q, a, b, g)

dmbbefdR(x, a, b, log=FALSE)
pmbbefdR(q, a, b, lower.tail = TRUE, log.p = FALSE)
qmbbefdR(p, a, b, lower.tail = TRUE, log.p = FALSE)
rmbbefdR(n, a, b)
ecmbbefdR(x, a, b)
mmbbefdR(order, a, b)
tlmbbefdR(a, b)
dMBBEFDR(x, g, b, log=FALSE)
pMBBEFDR(q, g, b, lower.tail = TRUE, log.p = FALSE)
qMBBEFDR(p, g, b, lower.tail = TRUE, log.p = FALSE)
rMBBEFDR(n, g, b)
ecMBBEFDR(x, g, b)
mMBBEFDR(order, g, b)
tlMBBEFDR(g, b)

Arguments

x, q

vector of quantiles.

p

vector of probabilities.

n

number of observations. If length(n) > 1, the length is take to be the number required.

a, b, g

shape parameters. For .mbbefd functions, g is computed from a.

order

order of the raw moment.

log, log.p

logical; if TRUE, probabilities p are given as log(p).

lower.tail

logical; if TRUE (default), probabilities are $P[X <= x]$,="" otherwise,="" $p[x=""> x]$.

Value

• A numeric value or a vector.

Details

it shall be remebered that $g=\frac{1}{p_1}=\frac{a+b}{\left(a+1\right)*b}$.

References

BERNEGGER, STEFAN. THE SWISS RE EXPOSURE CURVES AND THE MBBEFD DISTRIBUTION CLASS. Astin Bulletin (1997): 99.

See Also

swissRe, mbbefdExposure

Examples

#few examples of the functions
aPar=0.2
bPar=0.04
rmbbefd(n=1000,a=aPar,b=bPar) #for random generation
qmbbefd(p=0.7,a=aPar,b=bPar) #for quantiles
dmbbefd(x=0.5,b=.04,g=20) #for density
pmbbefd(q=0.5,b=.04,g=20) #for distribution function