文章基本信息
- 标题：MCMC and GLMs for estimating regression parameters: Evidence from non-life Egyptian insurance sector
- 本地全文：下载
- 作者：Mahmoud ELsayed ; Amr Soliman
- 期刊名称：Journal of Humanities and Applied Social Sciences
- 电子版ISSN：2632-279X
- 出版年度：2019
- 卷号：2
- 期号：1
- 页码：46-55
- DOI：10.1108/JHASS-08-2019-0028
- 出版社：Emerald Publishing
- 摘要：Purpose – The purpose of this study is to estimate the linear regression parameters using two alternative techniques. First technique is to apply the generalized linear model (GLM) and the second technique is the Markov Chain Monte Carlo (MCMC) method. Design/methodology/approach – In this paper, the authors adopted the incurred claims of Egyptian non-life insurance market as a dependent variable during a 10-year period. MCMC uses Gibbs sampling to generate a sample from a posterior distribution of a linear regression to estimate the parameters of interest. However, the authors used the R package to estimate the parameters of the linear regression using the above techniques. Findings – These procedures will guide the decision-maker for estimating the reserve and set proper investment strategy. Originality/value – In this paper, the authors will estimate the parameters of a linear regression model using MCMC method via R package. Furthermore, MCMC uses Gibbs sampling to generate a sample from a posterior distribution of a linear regression to estimate parameters to predict future claims. In the same line, these procedures will guide the decision-maker for estimating the reserve and set proper investment strategy.
- 其他摘要：
Purpose The purpose of this study is to estimate the linear regression parameters using two alternative techniques. First technique is to apply the generalized linear model (GLM) and the second technique is the Markov Chain Monte Carlo (MCMC) method.
Design/methodology/approach In this paper, the authors adopted the incurred claims of Egyptian non-life insurance market as a dependent variable during a 10-year period. MCMC uses Gibbs sampling to generate a sample from a posterior distribution of a linear regression to estimate the parameters of interest. However, the authors used the R package to estimate the parameters of the linear regression using the above techniques.
Findings These procedures will guide the decision-maker for estimating the reserve and set proper investment strategy.
Originality/value In this paper, the authors will estimate the parameters of a linear regression model using MCMC method via R package. Furthermore, MCMC uses Gibbs sampling to generate a sample from a posterior distribution of a linear regression to estimate parameters to predict future claims. In the same line, these procedures will guide the decision-maker for estimating the reserve and set proper investment strategy.
- 关键词：Insurance; Regression; Sampling; MCMC; GLM
