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

Autor:	Nor Farid Mohd Noor, Nor Azlida Aleng, Wan Muhammad Amir bin Wan Ahmad, Farah Muna Mohamad Ghazali
Rok vydání:	2021
Předmět:	Small data Bootstrapping (electronics) Exponential growth Computer Networks and Communications Hardware and Architecture Regression analysis Interval (mathematics) Algorithm Fuzzy logic Nonlinear regression Software Robust regression Mathematics
Zdroj:	Bulletin of Applied Mathematics and Mathematics Education. 1:1
ISSN:	2776-1029 2776-1002
DOI:	10.12928/bamme.v1i1.3853
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::3ca492d1c8e6650911800d39f50705c0 https://doi.org/10.12928/bamme.v1i1.3853 Zobrazit plný text záznamu