# MRbeta: McDonald-Richards beta distribution In VaRES: Computes value at risk and expected shortfall for over 100 parametric distributions

## Description

Computes the pdf, cdf, value at risk and expected shortfall for the McDonald-Richards beta distribution due to McDonald and Richards (1987a, 1987b) given by

\begin{array}{ll} &\displaystyle f (x) = \frac {x^{ar - 1} ≤ft( bq^r - x^r \right)^{b - 1}} {≤ft( b q^r \right)^{a + b - 1} B (a, b)}, \\ &\displaystyle F (x) = I_{\frac {x^r}{b q^r}} (a, b), \\ &\displaystyle {\rm VaR}_p (X) = b^{1/r} q ≤ft[ I_p^{-1} (a, b) \right]^{1/r}, \\ &\displaystyle {\rm ES}_p (X) = \frac {b^{1/r} q}{p} \int_0^p ≤ft[ I_v^{-1} (a, b) \right]^{1/r} dv \end{array}

for 0 ≤q x ≤q b^{1 / r} q, 0 < p < 1, q > 0, the scale parameter, a > 0, the first shape parameter, b > 0, the second shape parameter, and r > 0, the third shape parameter.

## Usage

 1 2 3 4 dMRbeta(x, a=1, b=1, r=1, q=1, log=FALSE) pMRbeta(x, a=1, b=1, r=1, q=1, log.p=FALSE, lower.tail=TRUE) varMRbeta(p, a=1, b=1, r=1, q=1, log.p=FALSE, lower.tail=TRUE) esMRbeta(p, a=1, b=1, r=1, q=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 q the value of the scale parameter, must be positive, the default is 1 a the value of the first shape parameter, must be positive, the default is 1 b the value of the second shape parameter, must be positive, the default is 1 r the value of the third shape 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

## Value

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.

## Author(s)

 1 2 3 4 5 x=runif(10,min=0,max=1) dMRbeta(x) pMRbeta(x) varMRbeta(x) esMRbeta(x)