An Alternative Algorithm for Linear Regression Modeling for Efficient Decision: A New Strategy of Handling Insurance Data


  • Mohamad Arif Awang Nawi
  • Wan Muhamad Amir W Ahmad
  • Mohamad Shafiq Mohd Ibrahim
  • Mustafa Mamat
  • Rabiatul Adawiyah Abdul Rohim
  • Mohamad Afendee Mohamed
  • . .



Multiple Linear Regression, Bootstrap method, Fuzzy Regression.


The multiple linear regression model is an important tool for investigating relationships between several response variables and some predictor variables. The primary interest is in inference about the unknown regression coefficient matrix. In this paper, we propose to combine and compare multiple linear regression, bootstrapping and fuzzy regression methods to build alternative methods. We formalize this extension and prove its validity. A real data example and two simulated data examples, which offer some finite sample verification of our theoretical results are provided. The results, based on significant value and average width showed alternative methods produce better results than multiple linear regressions (MLR) model.




[1] Ahmad WMAW, Nawi MAA & Aleng NA (2013), Relative efficiency analysis industry of life and general insurance in Malaysia using Stochastic Frontier Analysis (SFA). Applied Mathematical Sciences, 7(23), 1107-1118.

[2] Alan OS (1993), An introduction to regression analysis. Coase-Sandor Institute for Law and Economics Working Paper No. 20.

[3] Bargiela A, Pedrycz W & Nakashima T (2007), Multiple regression with fuzzy data. Fuzzy Sets and Systems, 158(19), 2169-2188.

[4] Efron B & Tibshyrani RJ (1993), An introduction to the bootstrap. Chapman and Hall.

[5] Goncalves S & White H (2005), Bootstrap standard error estimates for linear regression. J. Am. Stat. Assoc., 100, 970-979.

[6] Hall P (1992), The bootstrap and edgeworth expansion. Springer Verlag.

[7] Hoffmann JP (2010), Linear regression analysis: Applications and assumptions. Brigham Young University.

[8] Kacprzyk J & Fedrizzi M (1992), Fuzzy regression analysis. Omnitech Press.

[9] Kim KJ, Moskowitz H & Koksalan M (1996), Fuzzy versus statistical linear regression. European Journal of Operation Research, 92(2), 417-437.

[10] Tanaka H, Uejima S & Asai K (1982), Linear regression analysis with fuzzy model. IEEE Transactions on Systems, Man and Cybernetics, 12(6), 903-907.

[11] Marza V & Seyyedi MA (2009), Fuzzy multiple regression model for estimating software development time. International Journal of Engineering Business Management, 1(2), 31-34.

View Full Article:

How to Cite

Arif Awang Nawi, M., Muhamad Amir W Ahmad, W., Shafiq Mohd Ibrahim, M., Mamat, M., Adawiyah Abdul Rohim, R., Afendee Mohamed, M., & ., . (2018). An Alternative Algorithm for Linear Regression Modeling for Efficient Decision: A New Strategy of Handling Insurance Data. International Journal of Engineering & Technology, 7(3.28), 343–347.
Received 2019-02-12
Accepted 2019-02-12