Fuzzy regression model with Bayesian approach and its application to public health data

Authors

  • Wan Muhammad Amir bin Wan Ahmad Universiti Sains Malaysia
  • Nurul Asyikin Nizam Akbar Universiti Sains Malaysia
  • Farah Muna Mohamad Ghazali Universiti Sains Malaysia
  • Nor Farid Mohd Noor Universiti Sains Malaysia
  • Nor Azlida Aleng Universiti Malaysia Terengganu

DOI:

https://doi.org/10.12928/bamme.v2i1.3953

Keywords:

Bootstrap, Bayesian linear regression, Fuzzy regression

Abstract

The application of the Bayesian Linear Regression (BLR) and Fuzzy Bayesian Linear Regression method through the SAS algorithm is the focus of this paper. As an alternative method of data analysis in biostatistics, this modified method can be used. This modified method includes a bootstrapping technique, residual normality checking and some Bayesian Linear Regression Modeling (BLR) enhancement through Fuzzy Bayesian Linear Regression. We illustrated the application of the algorithm for Bayesian Linear Regression (BLR) and Fuzzy Bayesian Linear Regression in this paper.

References

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Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis, third edition. USA: CRC Press.

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Modified Bayesian linear regression flowchart

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Published

2022-05-18

Issue

Vol. 2 No. 1 (2022)

Section

Articles

License

Copyright (c) 2022 Wan Muhammad Amir bin Wan Ahmad, Nurul Asyikin Nizam Akbar, Farah Muna Mohamad Ghazali, Nor Farid Mohd Noor, Mohamad Arif Awang, Nor Azlida Aleng

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