buildMixingSevdist: Building a dynamic mixture model as a sevdist object In OpVaR: Statistical Methods for Modeling Operational Risk

Description

Building a dynamic mixture model as a sevdist object

Usage

 `1` ``` buildMixingSevdist(body.distr, body.param, tail.distr, tail.param, mixing.param) ```

Arguments

 `body.distr` A string giving the name of the body distribution. `body.param` Vector of the parameters for the given body distribution. `tail.distr` A string giving the name of the tail distribution. `tail.param` Vector of the parameters for the given tail distribution. Distributions "lgamma", "weibull", "gpd", "gh" are recognised. `mixing.param` Vector of the parameters for the given mixing distribution.

Details

A sevdist object with type 'mixing' is generated, i.e. the distribution of the severity is a dynamic mixture of the distributions 'body.distr' with parameters given by 'body.param' and 'tail.distr' with parameters given by 'tail.param' using the cdf of a mixing distribution 'mixing.distr' with parameters 'mixing.param' according to Frigessi et al. (2002).

The density f(x) for a dynamic mixture model with body distribution having density g and tail distribution having density h and cumulative distribution function p of the mixing distribution is given below:

f(x) = C*[p(x)*g(x) +(1-p(x))*h(x)]

Christina Zou

References

Frigessi, A., Haug, O., & Rue, H. (2002). A dynamic mixture model for unsupervised tail estimation without threshold selection. Extremes, 5(3), 219-235.

Examples

 ```1 2 3 4``` ``` # Create mixing sevdist object sevdist = buildMixingSevdist("weibull", c(2,6), "gpd", c(0,4,-0.5), c(8,.8)) # Plot pdf plot(sevdist) ```

OpVaR documentation built on May 29, 2018, 9:04 a.m.