Library: | times |
See also: | simNHPP simNHPPRP simNHPPRPedf simNHPPRPmeanloss simNHPPRPedfRT simNHPPRPRT |
Quantlet: | simNHPPRPmeanlossRT | |
Description: | plots real-life trajectory of the risk process from given data with the premium corresponding to non-homogeneous Poisson process and incorporating given mean loss value. |
Usage: | y = simNHPPRPmeanlossRT(u,theta,lambda,parlambda,time,val,meanloss,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) | |
time | p x 1 vector, occurence times of empirical losses | |
val | p x 1 vector, empirical losses | |
meanloss | scalar, mean loss incorporated in the premium | |
T | scalar, time horizon | |
Output: | ||
y | 2*max+2 x N x 2 array, generated process - max is the maximum number of jumps for all generated trajectories |
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=simNHPPRPmeanlossRT(10,0.2,0,#(1,1,0),arttime,artlossvals,1.5,20) 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 the given data with the premium corresponding to the non-homogeneous Poisson process and incorporating given mean loss value.