Nonlinear Split-Plot Design Model in Parameters Estimation using Estimated Generalized Least Square - Maximum Likelihood Estimation
This research aimed to provide a theoretical framework for intrinsically nonlinear models with two additive error terms. To achieve this, an iterative Gauss-Newton via Taylor Series expansion procedures for Estimated Generalized Least Square (EGLS) technique was adopted. This technique was applied i...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Bina Nusantara University
2018-12-01
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| Series: | ComTech |
| Subjects: | |
| Online Access: | https://journal.binus.ac.id/index.php/comtech/article/view/4703 |
| _version_ | 1797727013533908992 |
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| author | Ikwuoche John David Osebekwin Ebenenzer Asiribo Hussain Garba Dikko |
| author_facet | Ikwuoche John David Osebekwin Ebenenzer Asiribo Hussain Garba Dikko |
| author_sort | Ikwuoche John David |
| collection | DOAJ |
| description | This research aimed to provide a theoretical framework for intrinsically nonlinear models with two additive error terms. To achieve this, an iterative Gauss-Newton via Taylor Series expansion procedures for Estimated Generalized Least Square (EGLS) technique was adopted. This technique was applied in estimating the parameters of an intrinsically nonlinear split-plot design model where the variance components were unknown. The unknown variance components were estimated via Maximum Likelihood Estimation (MLE) method. To achieve the numerical stability in the iterative process of estimating the parameters, Householder QR decomposition was used. The results show that EGLS method presented in this research is available and applicable to estimate linear fixed, random, and mixed-effect models. However, in practical situations, the functional form of the mean in the model is often nonlinear due to the dynamics involved in the system process. |
| first_indexed | 2024-03-12T10:53:46Z |
| format | Article |
| id | doaj.art-af2fd41a898a474e86fb8c4f7363b335 |
| institution | Directory Open Access Journal |
| issn | 2087-1244 2476-907X |
| language | English |
| last_indexed | 2024-03-12T10:53:46Z |
| publishDate | 2018-12-01 |
| publisher | Bina Nusantara University |
| record_format | Article |
| series | ComTech |
| spelling | doaj.art-af2fd41a898a474e86fb8c4f7363b3352023-09-02T06:37:36ZengBina Nusantara UniversityComTech2087-12442476-907X2018-12-0192657110.21512/comtech.v9i2.47033417Nonlinear Split-Plot Design Model in Parameters Estimation using Estimated Generalized Least Square - Maximum Likelihood EstimationIkwuoche John David0Osebekwin Ebenenzer Asiribo1Hussain Garba Dikko2Ahmadu Bello University, Zaria.Ahmadu Bello University, Zaria.Ahmadu Bello University, Zaria.This research aimed to provide a theoretical framework for intrinsically nonlinear models with two additive error terms. To achieve this, an iterative Gauss-Newton via Taylor Series expansion procedures for Estimated Generalized Least Square (EGLS) technique was adopted. This technique was applied in estimating the parameters of an intrinsically nonlinear split-plot design model where the variance components were unknown. The unknown variance components were estimated via Maximum Likelihood Estimation (MLE) method. To achieve the numerical stability in the iterative process of estimating the parameters, Householder QR decomposition was used. The results show that EGLS method presented in this research is available and applicable to estimate linear fixed, random, and mixed-effect models. However, in practical situations, the functional form of the mean in the model is often nonlinear due to the dynamics involved in the system process.https://journal.binus.ac.id/index.php/comtech/article/view/4703split-plot design, parameters estimation, estimated generalized least square, maximum likelihood estimation |
| spellingShingle | Ikwuoche John David Osebekwin Ebenenzer Asiribo Hussain Garba Dikko Nonlinear Split-Plot Design Model in Parameters Estimation using Estimated Generalized Least Square - Maximum Likelihood Estimation ComTech split-plot design, parameters estimation, estimated generalized least square, maximum likelihood estimation |
| title | Nonlinear Split-Plot Design Model in Parameters Estimation using Estimated Generalized Least Square - Maximum Likelihood Estimation |
| title_full | Nonlinear Split-Plot Design Model in Parameters Estimation using Estimated Generalized Least Square - Maximum Likelihood Estimation |
| title_fullStr | Nonlinear Split-Plot Design Model in Parameters Estimation using Estimated Generalized Least Square - Maximum Likelihood Estimation |
| title_full_unstemmed | Nonlinear Split-Plot Design Model in Parameters Estimation using Estimated Generalized Least Square - Maximum Likelihood Estimation |
| title_short | Nonlinear Split-Plot Design Model in Parameters Estimation using Estimated Generalized Least Square - Maximum Likelihood Estimation |
| title_sort | nonlinear split plot design model in parameters estimation using estimated generalized least square maximum likelihood estimation |
| topic | split-plot design, parameters estimation, estimated generalized least square, maximum likelihood estimation |
| url | https://journal.binus.ac.id/index.php/comtech/article/view/4703 |
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