BellEW distribution {ActuarialM}R Documentation

Bell exponentiated Weibull distribution

Description

Computes the value at risk and expected shortfall based on the Bell exponentiated Weibull (BellEW) distribution. The CDF of the Bell G family is as follows:

H(x)=\frac{1-\exp\left[-e^{\lambda}\left(1-e^{-\lambda K(x)}\right)\right]}{1-\exp\Bigl(1-e^{\lambda}\Bigr)};\qquad\lambda>0,

where K(x) represents the baseline exponentiated Weibull CDF, it is given by

K(x)=\left[1-\exp(-\alpha x^{\beta})\right]^{\theta};\qquad\alpha,\beta,\theta>0.

By setting K(x) in the above Equation, yields the CDF of the BellEW distribution. The following expression can be used to calculate the VaR:

VaR_{p}(X)=\left[\frac{-1}{\alpha}\ln\left(1-\left[1-\left(\frac{1}{\lambda}\left[\ln\left(\left[\ln\left(1-p\left[1-\exp\Bigl(1-e^{\lambda}\Bigr)\right]\right)\right]+e^{\lambda}\right)\right]\right)\right]^{1/\theta}\right)\right]^{1/\beta},

where p \in (0,1). The ES can be computed from the following expression:

ES_{p}(X)=\frac{1}{p}\intop_{0}^{p}\left[\frac{-1}{\alpha}\ln\left(1-\left[1-\left(\frac{1}{\lambda}\left[\ln\left(\left[\ln\left(1-z\left[1-\exp\Bigl(1-e^{\lambda}\Bigr)\right]\right)\right]+e^{\lambda}\right)\right]\right)\right]^{1/\theta}\right)\right]^{1/\beta}dz.

Usage

vBellEW(p, alpha, beta, theta,lambda, log.p = FALSE, lower.tail = TRUE)
eBellEW(p, alpha, beta, theta,lambda)

Arguments

p

A vector of probablities p \in (0,1).

lambda

The strictly positive parameter of the Bell G family of distributions \lambda > 0.

alpha

The strictly positive scale parameter of the baseline exponentiated Weibull distribution (\alpha > 0).

beta

The strictly positive shape parameter of the baseline exponentiated Weibull distribution (\beta > 0).

theta

The strictly positive shape parameter of the baseline exponentiated Weibull distribution (\theta > 0).

lower.tail

if FALSE then 1-H(x) are returned and quantiles are computed for 1-p.

log.p

if TRUE then log(H(x)) are returned and quantiles are computed for exp(p).

Details

The functions allow to compute the value at risk and the expected shortfall of the BellEW distribution.

Value

vBellEW gives the value at risk. eBellEW gives the expected shortfall.

Author(s)

Muhammad Imran and M.H. Tahir.

R implementation and documentation: Muhammad Imran imranshakoor84@yahoo.com and M.H. Tahir mht@iub.edu.pk.

References

Fayomi, A., Tahir, M. H., Algarni, A., Imran, M., & Jamal, F. (2022). A new useful exponential model with applications to quality control and actuarial data. Computational Intelligence and Neuroscience, 2022.

Alsadat, N., Imran, M., Tahir, M. H., Jamal, F., Ahmad, H., & Elgarhy, M. (2023). Compounded Bell-G class of statistical models with applications to COVID-19 and actuarial data. Open Physics, 21(1), 20220242.

Nadarajah, S., Cordeiro, G. M., & Ortega, E. M. (2013). The exponentiated Weibull distribution: a survey. Statistical Papers, 54, 839-877.

See Also

eBellW, eBellEE

Examples

p=runif(10,min=0,max=1)
vBellEW(p,1,1,2,1)
eBellEW(p,1,1,2,1)

[Package ActuarialM version 0.1.0 Index]