moexp function

Marshall-Olkin exponential distribution

Marshall-Olkin exponential distribution

Computes the pdf, cdf, value at risk and expected shortfall for the Marshall-Olkin exponential distribution due to Marshall and Olkin (1997) given by [REMOVE_ME]\displaystylef(x)=λexp(λx)[exp(λx)1+a]2,\displaystyleF(x)=exp(λx)2+aexp(λx)1+a,VaRp(X)=1λlog2a(1a)p1p,ESp(X)=1λlog[2a(1a)p]2aλ(1a)plog2a(1a)p2a+1pλplog(1p)[REMOVEME2] \begin{array}{ll}&\displaystylef (x) = \frac {\displaystyle \lambda \exp (\lambda x)}{\displaystyle \left[ \exp (\lambda x) - 1 + a \right]^2},\\&\displaystyleF (x) = \frac {\displaystyle \exp (\lambda x) - 2 + a}{\displaystyle \exp (\lambda x) - 1 + a},\\&\displaystyle{\rm VaR}_p (X) = \frac {1}{\lambda} \log \frac {2 - a - (1 - a) p}{1 - p},\\&\displaystyle{\rm ES}_p (X) = \frac {1}{\lambda} \log\left[ 2 - a - (1 - a) p \right] - \frac {2 - a}{\lambda (1 - a) p}\log \frac {2 - a - (1 - a) p}{2 - a} + \frac {1 - p}{\lambda p} \log (1 - p)\end{array} [REMOVE_ME_2]

for x>0x > 0, 0<p<10 < p < 1, a>0a > 0, the first scale parameter and λ>0\lambda > 0, the second scale parameter.

Description

Computes the pdf, cdf, value at risk and expected shortfall for the Marshall-Olkin exponential distribution due to Marshall and Olkin (1997) given by

\displaystylef(x)=λexp(λx)[exp(λx)1+a]2,\displaystyleF(x)=exp(λx)2+aexp(λx)1+a,VaRp(X)=1λlog2a(1a)p1p,ESp(X)=1λlog[2a(1a)p]2aλ(1a)plog2a(1a)p2a+1pλplog(1p) \begin{array}{ll}&\displaystylef (x) = \frac {\displaystyle \lambda \exp (\lambda x)}{\displaystyle \left[ \exp (\lambda x) - 1 + a \right]^2},\\&\displaystyleF (x) = \frac {\displaystyle \exp (\lambda x) - 2 + a}{\displaystyle \exp (\lambda x) - 1 + a},\\&\displaystyle{\rm VaR}_p (X) = \frac {1}{\lambda} \log \frac {2 - a - (1 - a) p}{1 - p},\\&\displaystyle{\rm ES}_p (X) = \frac {1}{\lambda} \log\left[ 2 - a - (1 - a) p \right] - \frac {2 - a}{\lambda (1 - a) p}\log \frac {2 - a - (1 - a) p}{2 - a} + \frac {1 - p}{\lambda p} \log (1 - p)\end{array}

for x>0x > 0, 0<p<10 < p < 1, a>0a > 0, the first scale parameter and λ>0\lambda > 0, the second scale parameter.

dmoexp(x, lambda=1, a=1, log=FALSE) pmoexp(x, lambda=1, a=1, log.p=FALSE, lower.tail=TRUE) varmoexp(p, lambda=1, a=1, log.p=FALSE, lower.tail=TRUE) esmoexp(p, lambda=1, a=1)

Arguments

  • x: scaler or vector of values at which the pdf or cdf needs to be computed
  • p: scaler or vector of values at which the value at risk or expected shortfall needs to be computed
  • a: the value of the first scale parameter, must be positive, the default is 1
  • lambda: the value of the second scale parameter, must be positive, the default is 1
  • log: if TRUE then log(pdf) are returned
  • log.p: if TRUE then log(cdf) are returned and quantiles are computed for exp(p)
  • lower.tail: if FALSE then 1-cdf are returned and quantiles are computed for 1-p

Returns

An object of the same length as x, giving the pdf or cdf values computed at x or an object of the same length as p, giving the values at risk or expected shortfall computed at p.

References

Stephen Chan, Saralees Nadarajah & Emmanuel Afuecheta (2016). An R Package for Value at Risk and Expected Shortfall, Communications in Statistics - Simulation and Computation, 45:9, 3416-3434, tools:::Rd_expr_doi("10.1080/03610918.2014.944658")

Author(s)

Saralees Nadarajah

Examples

x=runif(10,min=0,max=1) dmoexp(x) pmoexp(x) varmoexp(x) esmoexp(x)
  • Maintainer: Leo Belzile
  • License: GPL (>= 2)
  • Last published: 2023-04-22

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