| Library: | times |
| See also: | simNHPP simNHPPRP simNHPPRPedf simNHPPRPmeanloss simNHPPRPedfRT simNHPPRPmeanlossRT |
| Quantlet: | simNHPPRPRT | |
| Description: | plots real-life trajectory of the risk process from given data with the premium corresponding to non-homogeneous Poisson process. |
| Usage: | y = simNHPPRPRT(u,theta,lambda,parlambda,distrib,params,time,val,T) | |
| Input: | ||
| u | scalar, initial capital | |
| theta | scalar, relative safety loading | |
| lambda | scalar, intensity function, sine function (lambda=0), linear function (lambda=1), or sine square function (lambda=2) | |
| parlambda | n x 1 vector, parameters of the intensity function lambda (n=2 for lambda=1, n=3 otherwise) | |
| distrib | string, claim size distribution | |
| params | n x 1 vector, parameters of the claim size distribution, n=1 (exponential), n=2 (gamma, lognormal, Pareto, Weibull), n=3 (Burr, mixofexps) | |
| time | p x 1 vector, occurence times of empirical losses | |
| val | p x 1 vector, empirical losses | |
| T | scalar, time horizon | |
| Output: | ||
| y | 2*p+2 x 1 x 2 array, generated trajectory of the risk process | |
library("xplore")
library("times")
library("plot")
randomize2(101)
randomize(101)
arttime=cumsum(rndexp(100,1,1))
arttime=paf(arttime,arttime<=20)
artlossvals=rndBurr(size(arttime),1,3,2,1)
y1=simNHPPRPRT(10,0.2,0,#(1,1,0),"gamma",#(2,3),arttime,artlossvals,20)
y1=reduce(y1)
d1 = createdisplay(1,1)
adddata(d1, 1, 1,setmask(y1,"line","medium","red", "style",1))
Show real-life trajectory of the risk process from given data with the premium corresponding to non-homogeneous Poisson process.