Usage: |
y = INSSegerdahl(u, T, lambda, theta, distrib, dparameters)
|
Input: |
| u | scalar, n x 1 vector or m x n matrix, initial capital for risk process
|
| T | scalar or p x 1 vector (only if u is a vector or scalar), time horizon for risk process
|
| lambda | scalar, intensity of loss arrivals driven by Poisson process
|
| theta | scalar, security loading in insurance collective risk model
|
| distrib | string, name of light tailed distribution of claims, either:
gamma, exponential or mixofexps
|
| dparameters | list of scalars, parameters of the following distributions: exponential, gamma
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, p x 1 or n x 1 vector (size of T or u) or p x n matrix or m x n matrix,
ruin probability in finite time horizon T given by Segerdahl approximation. |
- Example:
library("insurance")
library("xplore")
distrib = "gamma"
dparameters = list(0.2,0.7)
u = #(1:10)
T = 100
lambda = 5
theta = 0.3
y = INSSegerdahl(u, T, lambda, theta, distrib, dparameters)
y
- Result:
Contents of y
[ 1,] 0.55717
[ 2,] 0.43219
[ 3,] 0.33524
[ 4,] 0.26004
[ 5,] 0.20171
[ 6,] 0.15646
[ 7,] 0.12136
[ 8,] 0.094138
[ 9,] 0.073021
[10,] 0.056641
- Example:
library("insurance")
library("xplore")
distrib = "gamma"
dparameters = list(0.2,0.7)
u = #(1:5)
T = #(1:10)
lambda = 5
theta = 0.3
y = INSSegerdahl(u, T, lambda, theta, distrib, dparameters)
y
- Result:
Contents of y
[ 1,] 0.2517 0.16541 0.11341 0.079176 0.055858
[ 2,] 0.2915 0.18667 0.12636 0.087517 0.0614
[ 3,] 0.33088 0.2084 0.13974 0.09618 0.067174
[ 4,] 0.36863 0.23025 0.15341 0.1051 0.073151
[ 5,] 0.40366 0.25187 0.16723 0.11423 0.079299
[ 6,] 0.43515 0.27293 0.18106 0.12347 0.085582
[ 7,] 0.46256 0.29311 0.19474 0.13277 0.091962
[ 8,] 0.48567 0.31214 0.20814 0.14205 0.098399
[ 9,] 0.50453 0.3298 0.22112 0.15123 0.10485
[10,] 0.51945 0.34594 0.23355 0.16024 0.11128