Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

 Quantlet: simNHPPRPRT Description: plots real-life trajectory of the risk process from given data with the premium corresponding to non-homogeneous Poisson process.

Reference(s):
K. Burnecki, R.Weron (2004) "Modeling of the risk process", in “Statistical Tools for Finance and Insurance”, eds. P. Cizek, W. Härdle, R. Weron, Springer.

 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

Example:
```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)
```Show real-life trajectory of the risk process from