bgr.sim: Simulated artificial data based on bivariate gamma regression...

In senhu/mvClaim: Multivariate general insurance claims modelling

Description

An artificial data set of size 1000 containing the bivariate response y1, y2, three covariates w1, w2, w3.

Usage

bgr.sim

Format

A data frame with 1000 rows and 5 variables:

y1,y2

The bivariate response variable.

w1,w2,w3

Three covariates.

Details

This data set of size 1000 is artificially generated as following: first w1, w2, and w3 are simulated from Normal(0, 1). Then the α1, α2, α3, β are generated via

α1 = exp(1 + 0.1 w1 + 0.3 w2)

α2 = exp(0.1 + 0.1 w2 + 0.1 w3)

α3 = exp(0.5 + 0.1 w1 + 0.2 w2 + 0.4 w3)

β = exp(0.2 + 0.1 w1 + 0.1 w2 + 0.2 w3)

For each set of parameters (α1, α2, α3, β) a random sample from this bivariate gamma distribution is simulated, i.e. y ~ BG(α1, α2, α3, β).

Source

Hu, S., Murphy, T. B. and O'Hagan, A. (2019) Bivariate Gamma Mixture of Experts Models for Joint Claims Modeling. To appear.

senhu/mvClaim documentation built on Jan. 29, 2022, 3:18 p.m.