XploRe Help : INShtraffic

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

Library:	insurance
See also:	INSltraffic INShltraffic

Quantlet:		INShtraffic
Description:		produces the heavy traffic (diffusion) approximation of ruin probability in infinite time for insurance collective risk model.

Reference(s):

P. Cizek, W. Haerdle, R. Weron (2004): "Statistical Tools for Finance and Insurance"

Usage:	`y = INShtraffic(u, theta, distrib, dparameters)`
Input:
	`u`	scalar, n x 1 vector or m x n matrix, initial capital for risk process
	`theta`	scalar, security loading in insurance collective risk model
	`distrib`	string, name of distribution of claims, either: exponential, gamma, mixofexps, Weibull, lognormal, loggamma, Pareto, Burr or truncPareto.
	`dparameters`	list of scalars, parameters of the following distributions: exponential, gamma, Weibull, lognormal, loggamma, Pareto, Burr or truncPareto list of n x 1 vectors of parameters of "mixofexps" distribution, the first vector are parameters for the exponential distributions and the second one are the weights of mixing.
Output:
	`y`	scalar, n x 1 vector or m x n matrix (same dimension as u), ruin probability given by heavy traffic approximation.

Note:

In this example the loss distribution is chosen to be gamma, safety loading 0.3 and initial capital a vector of values from 0 to 10. The heavy traffic approximation exists if the first 2 raw moments of loss distribution exist.

Example:

library("insurance") library("distribs") distrib = "gamma" dparameters = list(0.2,0.7) u = #(0:10) theta = 0.3 y = INShtraffic(u, theta, distrib, dparameters) y

Result:

Contents of y

[ 1,]          1
[ 2,]    0.70469
[ 3,]    0.49659
[ 4,]    0.34994
[ 5,]    0.2466
[ 6,]    0.17377
[ 7,]    0.12246
[ 8,]    0.086294
[ 9,]    0.06081
[10,]    0.042852
[11,]    0.030197

Author: P. Mista, 20031218 license MD*Tech