Pembangunan dimensi baru bagi model regresi eksponen (kreb): aplikasi dalam sains kesihatan

The exponential regression method is a non-linear regression method that is commonly used in the field of biometrics. Generally, the exponential regression model is often applied in research especially in estimating the growth rate of bacteria and viruses. Similar to the linear regression method,...

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Main Author:	Rohim, Rabi'atul 'Adawiyah Abdul
Format:	Thesis
Language:	English
Published:	2020
Subjects:	R Medicine
Online Access:	http://eprints.usm.my/48113/1/61.%20RABI%27ATUL%27ADAWIYAH%20BINTI%20ABDUL%20ROHIM%20%20-%20FINAL%20THESIS%20P-SGD000518%28R%29%20PWD%20NO%20MATRIK_-24%20pages.pdf
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id	my-usm-ep.48113
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spelling	my-usm-ep.481132021-01-17T05:09:35Z Pembangunan dimensi baru bagi model regresi eksponen (kreb): aplikasi dalam sains kesihatan 2020-09 Rohim, Rabi'atul 'Adawiyah Abdul R Medicine The exponential regression method is a non-linear regression method that is commonly used in the field of biometrics. Generally, the exponential regression model is often applied in research especially in estimating the growth rate of bacteria and viruses. Similar to the linear regression method, the exponential regression model also involves the relationship between two situations that can be explained in terms of independent and dependent variables. Fundamentally, this non-linear relationship (exponential relationship) can be embodied or transformed into a linear form (linear equation). Through this transformation step, the efficiency of a model function can be improved and enhanced. The main focus of this study is to establish a standard procedure for integrated exponential function algorithm, the KREB Model, with emphasis on the modelling techniques based on the scientific computational statistical method and the advanced statistical method by utilising the SAS software. The KREB Model is short for Integrated Exponential Regression Method. Essentially, this study combines several advanced statistical methods that are integrated into a single SAS programming language involving the exponential method, the bootstrap method as well as fuzzy regression. An in-depth analysis of all three cases was carried out and the results were compared thoroughly. The outcome from the KREB Model was relatively compared with the existing methods. The findings from the comparison will provide information regarding the effectiveness of the KREB Model. The KREB Model has a smaller average interval than the existing model. The KREB Model developed is better than the existing model and can make predictions more efficiently and accurately. Future research proposals can be expanded by using exponentialregression methods by creating a KREB Model based on partial regregssion, spatial regression and poison regression so that it can be used as a guide in future research. In conclusion, the KREB Model that was developed has successfully optimised the results of the study through the computational statistical calculation method. 2020-09 Thesis http://eprints.usm.my/48113/ http://eprints.usm.my/48113/1/61.%20RABI%27ATUL%27ADAWIYAH%20BINTI%20ABDUL%20ROHIM%20%20-%20FINAL%20THESIS%20P-SGD000518%28R%29%20PWD%20NO%20MATRIK_-24%20pages.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Kesihatan
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	R Medicine
spellingShingle	R Medicine Rohim, Rabi'atul 'Adawiyah Abdul Pembangunan dimensi baru bagi model regresi eksponen (kreb): aplikasi dalam sains kesihatan
description	The exponential regression method is a non-linear regression method that is commonly used in the field of biometrics. Generally, the exponential regression model is often applied in research especially in estimating the growth rate of bacteria and viruses. Similar to the linear regression method, the exponential regression model also involves the relationship between two situations that can be explained in terms of independent and dependent variables. Fundamentally, this non-linear relationship (exponential relationship) can be embodied or transformed into a linear form (linear equation). Through this transformation step, the efficiency of a model function can be improved and enhanced. The main focus of this study is to establish a standard procedure for integrated exponential function algorithm, the KREB Model, with emphasis on the modelling techniques based on the scientific computational statistical method and the advanced statistical method by utilising the SAS software. The KREB Model is short for Integrated Exponential Regression Method. Essentially, this study combines several advanced statistical methods that are integrated into a single SAS programming language involving the exponential method, the bootstrap method as well as fuzzy regression. An in-depth analysis of all three cases was carried out and the results were compared thoroughly. The outcome from the KREB Model was relatively compared with the existing methods. The findings from the comparison will provide information regarding the effectiveness of the KREB Model. The KREB Model has a smaller average interval than the existing model. The KREB Model developed is better than the existing model and can make predictions more efficiently and accurately. Future research proposals can be expanded by using exponentialregression methods by creating a KREB Model based on partial regregssion, spatial regression and poison regression so that it can be used as a guide in future research. In conclusion, the KREB Model that was developed has successfully optimised the results of the study through the computational statistical calculation method.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Rohim, Rabi'atul 'Adawiyah Abdul
author_facet	Rohim, Rabi'atul 'Adawiyah Abdul
author_sort	Rohim, Rabi'atul 'Adawiyah Abdul
title	Pembangunan dimensi baru bagi model regresi eksponen (kreb): aplikasi dalam sains kesihatan
title_short	Pembangunan dimensi baru bagi model regresi eksponen (kreb): aplikasi dalam sains kesihatan
title_full	Pembangunan dimensi baru bagi model regresi eksponen (kreb): aplikasi dalam sains kesihatan
title_fullStr	Pembangunan dimensi baru bagi model regresi eksponen (kreb): aplikasi dalam sains kesihatan
title_full_unstemmed	Pembangunan dimensi baru bagi model regresi eksponen (kreb): aplikasi dalam sains kesihatan
title_sort	pembangunan dimensi baru bagi model regresi eksponen (kreb): aplikasi dalam sains kesihatan
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Sains Kesihatan
publishDate	2020
url	http://eprints.usm.my/48113/1/61.%20RABI%27ATUL%27ADAWIYAH%20BINTI%20ABDUL%20ROHIM%20%20-%20FINAL%20THESIS%20P-SGD000518%28R%29%20PWD%20NO%20MATRIK_-24%20pages.pdf
_version_	1747821881752289280

Pembangunan dimensi baru bagi model regresi eksponen (kreb): aplikasi dalam sains kesihatan

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