Usage: |
y = INScordiffin(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, time horizon for risk process, vector allowed only when u is not a matrix
|
| 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 corrected diffusion 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 = INScordiffin(u, T, lambda, theta, distrib, dparameters)
y
- Result:
Contents of y
[ 1,] 0.55671
[ 2,] 0.43168
[ 3,] 0.33471
[ 4,] 0.25951
[ 5,] 0.20118
[ 6,] 0.15595
[ 7,] 0.12088
[ 8,] 0.09368
[ 9,] 0.07260
[10,] 0.05625
- 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 = INScordiffin(u, T, lambda, theta, distrib, dparameters)
y
- Result:
Contents of y
[ 1,] 0.23020 0.12563 0.06942 0.03870 0.02173
[ 2,] 0.32386 0.19397 0.11534 0.06827 0.04027
[ 3,] 0.37686 0.23967 0.15055 0.09366 0.05780
[ 4,] 0.41134 0.27214 0.17769 0.11473 0.07336
[ 5,] 0.43572 0.29638 0.19905 0.13218 0.08691
[ 6,] 0.45393 0.31515 0.21622 0.14675 0.09864
[ 7,] 0.46805 0.33011 0.23030 0.15904 0.10881
[ 8,] 0.47933 0.34229 0.24201 0.16950 0.11767
[ 9,] 0.48853 0.35240 0.25189 0.17848 0.12542
[10,] 0.49618 0.36090 0.26032 0.18626 0.13224