Modeling for exponential growth and decay methodology in biometry using SAS syntax

Authors

  • Wan Muhammad Amir bin Wan Ahmad 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.v1i1.3853

Keywords:

Bootstrap, fuzzy, robust regression, weighted

Abstract

This paper provided an alternative method for exponential growth modeling as a regression analysis technique through the SAS algorithm. This alternative method is a combination technique (using nonlinear model bootstrap and fuzzy regression) for the small data set and gives the researcher an option to start the analysis, even if there is not enough data set. This method enhances the previous methodology with embedded bootstrapping and fuzzy technique to a nonlinear regression model. This principle aims to propose an alternative method of analysis with better results. In our case, we applied this principle to farm data and compared the results obtained by looking at the average width of the predicted interval.

References

Diem Ngo, T. H., & La Puente, C. A. (2012). The steps to follow in a multiple regression analysis. SAS Global Forum 2012: Statistics and Data Analysis. Paper 333-2012, 1-12.

Cassel, D. L. (2010). Bootstrap Mania: Resampling the SAS. SAS Global Forum 2010: Statistics and Data Analysis. Paper 268-2010, 1-11.

Jung, B. C., Jhun, M., & Lee, J. W. (2005). Bootstrap Tests for Overdispersion in a Zero-Inflated Poisson Regression Model. Biometrics, 61, 626-629.

Kacprzyk J., & Fedrizzi, M. (1992). Fuzzy Regression Analysis. Warsaw: Omnitech Press.

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Published

2021-03-24

Issue

Vol. 1 No. 1 (2021)

Section

Articles

License

Copyright (c) 2021 Wan Muhammad Amir bin Wan Ahmad, Farah Muna Mohamad Ghazali, Nor Farid Mohd Noor, Nor Azlida Aleng

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