Estimasi Nonlinear Least Trimmed Squares (NLTS) pada Model Regresi Nonlinier yang Dikenai Outlier
Constant Elasticity of Substitution (CES) production function is the intrinsic nonlinear regression models that are often used to estimate the data in an industry. Intrinsic nonlinear regression model is a kind of nonlinear regression that can not be linearized, so as to estimate the beta parameters...
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| Format: | Article |
| Language: | English |
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Mathematics Department UIN Maulana Malik Ibrahim Malang
2015-11-01
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| Series: | Cauchy: Jurnal Matematika Murni dan Aplikasi |
| Subjects: | |
| Online Access: | https://ejournal.uin-malang.ac.id/index.php/Math/article/view/3170 |
| _version_ | 1811249609841836032 |
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| author | Nur Laili Arofah Sri Harini |
| author_facet | Nur Laili Arofah Sri Harini |
| author_sort | Nur Laili Arofah |
| collection | DOAJ |
| description | Constant Elasticity of Substitution (CES) production function is the intrinsic nonlinear regression models that are often used to estimate the data in an industry. Intrinsic nonlinear regression model is a kind
of nonlinear regression that can not be linearized, so as to estimate the beta parameters nonlinear statistical model used was Nonlinear Least Squares (NLS) using a first order taylor series approach used in the Gauss
Newton iteration. One of the problems often encountered in the analysis of data is an outlier, the presence of outliers in the data analysis greatly influence the results of the analysis so it becomes less valid and the estimation
become biased. One method that is resistant to outliers regression is a method of Nonlinear Least Trimmed Squares. This research aims to determine the characteristics of parameter CES production function which
contains outlier. The result shows that parameter of the production function CES which contains outliers are bias, inconsistent. So the CES production function which does not contain outliers better than the are contains
outliers. |
| first_indexed | 2024-04-12T15:49:36Z |
| format | Article |
| id | doaj.art-5275affae8854c18963e86e9bdb8afa6 |
| institution | Directory Open Access Journal |
| issn | 2086-0382 2477-3344 |
| language | English |
| last_indexed | 2024-04-12T15:49:36Z |
| publishDate | 2015-11-01 |
| publisher | Mathematics Department UIN Maulana Malik Ibrahim Malang |
| record_format | Article |
| series | Cauchy: Jurnal Matematika Murni dan Aplikasi |
| spelling | doaj.art-5275affae8854c18963e86e9bdb8afa62022-12-22T03:26:32ZengMathematics Department UIN Maulana Malik Ibrahim MalangCauchy: Jurnal Matematika Murni dan Aplikasi2086-03822477-33442015-11-0141222710.18860/ca.v4i1.31702789Estimasi Nonlinear Least Trimmed Squares (NLTS) pada Model Regresi Nonlinier yang Dikenai OutlierNur Laili Arofah0Sri Harini1Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Maulana Malik Ibrahim MalangJurusan Matematika, Fakultas Sains dan Teknologi, UIN Maulana Malik Ibrahim MalangConstant Elasticity of Substitution (CES) production function is the intrinsic nonlinear regression models that are often used to estimate the data in an industry. Intrinsic nonlinear regression model is a kind of nonlinear regression that can not be linearized, so as to estimate the beta parameters nonlinear statistical model used was Nonlinear Least Squares (NLS) using a first order taylor series approach used in the Gauss Newton iteration. One of the problems often encountered in the analysis of data is an outlier, the presence of outliers in the data analysis greatly influence the results of the analysis so it becomes less valid and the estimation become biased. One method that is resistant to outliers regression is a method of Nonlinear Least Trimmed Squares. This research aims to determine the characteristics of parameter CES production function which contains outlier. The result shows that parameter of the production function CES which contains outliers are bias, inconsistent. So the CES production function which does not contain outliers better than the are contains outliers.https://ejournal.uin-malang.ac.id/index.php/Math/article/view/3170nonlinear statistical modelparameter estimationconstant elasticity of substitution (ces) production functionoutliersnonlinear least trimmed square (nlts) method, gauss newton iteration |
| spellingShingle | Nur Laili Arofah Sri Harini Estimasi Nonlinear Least Trimmed Squares (NLTS) pada Model Regresi Nonlinier yang Dikenai Outlier Cauchy: Jurnal Matematika Murni dan Aplikasi nonlinear statistical model parameter estimation constant elasticity of substitution (ces) production function outliers nonlinear least trimmed square (nlts) method, gauss newton iteration |
| title | Estimasi Nonlinear Least Trimmed Squares (NLTS) pada Model Regresi Nonlinier yang Dikenai Outlier |
| title_full | Estimasi Nonlinear Least Trimmed Squares (NLTS) pada Model Regresi Nonlinier yang Dikenai Outlier |
| title_fullStr | Estimasi Nonlinear Least Trimmed Squares (NLTS) pada Model Regresi Nonlinier yang Dikenai Outlier |
| title_full_unstemmed | Estimasi Nonlinear Least Trimmed Squares (NLTS) pada Model Regresi Nonlinier yang Dikenai Outlier |
| title_short | Estimasi Nonlinear Least Trimmed Squares (NLTS) pada Model Regresi Nonlinier yang Dikenai Outlier |
| title_sort | estimasi nonlinear least trimmed squares nlts pada model regresi nonlinier yang dikenai outlier |
| topic | nonlinear statistical model parameter estimation constant elasticity of substitution (ces) production function outliers nonlinear least trimmed square (nlts) method, gauss newton iteration |
| url | https://ejournal.uin-malang.ac.id/index.php/Math/article/view/3170 |
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