Description Usage Arguments Details Author(s) References Examples
Building a dynamic mixture model as a sevdist object
1 | buildMixingSevdist(body.distr, body.param, tail.distr, tail.param, mixing.param)
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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. |
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
Frigessi, A., Haug, O., & Rue, H. (2002). A dynamic mixture model for unsupervised tail estimation without threshold selection. Extremes, 5(3), 219-235.
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)
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