A New Strategy of Handling General Insurance Modelling Using Applied Linear Method

  • Wan Muhamad Amir W Ahmad Universiti Sains Malaysia
  • Mohamad Arif Awang Nawi Universiti Sultan Zainal Abidin
  • Mustafa Mamat Universiti Sultan Zainal Abidin


This paper proposes the use of bootstrap, robust and fuzzy multiple linear regressions method in handling general insurance in order to get improved results. The main objective of bootstrapping is to estimate the distribution of an estimator or test statistic by resampling one's data or a model estimated from the data under conditions that hold in a wide variety of econometric applications. In addition, bootstrap also provides approximations to distributions of statistics, coverage probabilities of confidence intervals, and rejection probabilities of hypothesis tests that produce accurate results. In this paper, we emphasize the combining and modelling using bootstrapping, robust and fuzzy regression methodology. The results show that alternative methods produce better results than multiple linear regressions (MLR) model.


Keywords: Multiple linear regression; MM estimation; robust regression; bootstrap method; fuzzy regression

Author Biographies

Wan Muhamad Amir W Ahmad, Universiti Sains Malaysia
School of Dental Sciences
Mohamad Arif Awang Nawi, Universiti Sultan Zainal Abidin
Faculty Informatics and Computing
Mustafa Mamat, Universiti Sultan Zainal Abidin
Faculty Informatics and Computing


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How to Cite
W Ahmad, W. M. A., Awang Nawi, M. A., & Mamat, M. (2016). A New Strategy of Handling General Insurance Modelling Using Applied Linear Method. Malaysian Journal of Applied Sciences, 1(1), 45-54. Retrieved from https://journal.unisza.edu.my/myjas/index.php/myjas/article/view/22
Research Articles