Diagnostic Measures in Ridge Regression Model with AR(1) Errors under the Stochastic Linear Restrictions
Outliers and influential observations have important effects on the regression analysis. The goal of this paper is to extend the mean-shift model for detecting outliers in case of ridge regression model in the presence of stochastic linear restrictions when the error terms follow by an autoregressiv...
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University of Tehran
2018-01-01
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| Series: | Journal of Sciences, Islamic Republic of Iran |
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| Online Access: | https://jsciences.ut.ac.ir/article_64795_db39943b94dc78c3bb98470b3c5bb2e5.pdf |
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| author | A. Zaherzadeh Zaherzadeh A. R. Rasekh B. Babadi |
| author_facet | A. Zaherzadeh Zaherzadeh A. R. Rasekh B. Babadi |
| author_sort | A. Zaherzadeh Zaherzadeh |
| collection | DOAJ |
| description | Outliers and influential observations have important effects on the regression analysis. The goal of this paper is to extend the mean-shift model for detecting outliers in case of ridge regression model in the presence of stochastic linear restrictions when the error terms follow by an autoregressive AR(1) process. Furthermore, extensions of measures for diagnosing influential observations are derived. A numerical example of a real data set is used to illustrate the findings. Finally, a simulation study is conducted to evaluate the performance of the proposed procedure and measures. Results of this study show the efficiency of the proposed mean-shift outlier model for the proposed model. Also, the study resulted in some findings about the behavior of suggested measures for the specified model. In fact, these measures are affected by the degree of collinearity and the size of autocorrelation. |
| format | Article |
| id | doaj-art-68bcd6efdd1749a997e5c21380e226e4 |
| institution | OA Journals |
| issn | 1016-1104 2345-6914 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | University of Tehran |
| record_format | Article |
| series | Journal of Sciences, Islamic Republic of Iran |
| spelling | doaj-art-68bcd6efdd1749a997e5c21380e226e42025-08-20T01:53:09ZengUniversity of TehranJournal of Sciences, Islamic Republic of Iran1016-11042345-69142018-01-01291677810.22059/jsciences.2018.6479564795Diagnostic Measures in Ridge Regression Model with AR(1) Errors under the Stochastic Linear RestrictionsA. Zaherzadeh Zaherzadeh0A. R. Rasekh1B. Babadi2Department of Statistics, Faculty of Mathematical Sciences and Computer, Shahid Chamran University of Ahvaz, Ahvaz, Islamic Republic of IranDepartment of Statistics, Faculty of Mathematical Sciences and Computer, Shahid Chamran University of Ahvaz, Ahvaz, Islamic Republic of IranDepartment of Statistics, Faculty of Mathematical Sciences and Computer, Shahid Chamran University of Ahvaz, Ahvaz, Islamic Republic of IranOutliers and influential observations have important effects on the regression analysis. The goal of this paper is to extend the mean-shift model for detecting outliers in case of ridge regression model in the presence of stochastic linear restrictions when the error terms follow by an autoregressive AR(1) process. Furthermore, extensions of measures for diagnosing influential observations are derived. A numerical example of a real data set is used to illustrate the findings. Finally, a simulation study is conducted to evaluate the performance of the proposed procedure and measures. Results of this study show the efficiency of the proposed mean-shift outlier model for the proposed model. Also, the study resulted in some findings about the behavior of suggested measures for the specified model. In fact, these measures are affected by the degree of collinearity and the size of autocorrelation.https://jsciences.ut.ac.ir/article_64795_db39943b94dc78c3bb98470b3c5bb2e5.pdfridge regressionstochastic linear rrestrictionsautocorrelated error termsinfluential analysismean-shift outlier model |
| spellingShingle | A. Zaherzadeh Zaherzadeh A. R. Rasekh B. Babadi Diagnostic Measures in Ridge Regression Model with AR(1) Errors under the Stochastic Linear Restrictions Journal of Sciences, Islamic Republic of Iran ridge regression stochastic linear rrestrictions autocorrelated error terms influential analysis mean-shift outlier model |
| title | Diagnostic Measures in Ridge Regression Model with AR(1) Errors under the Stochastic Linear Restrictions |
| title_full | Diagnostic Measures in Ridge Regression Model with AR(1) Errors under the Stochastic Linear Restrictions |
| title_fullStr | Diagnostic Measures in Ridge Regression Model with AR(1) Errors under the Stochastic Linear Restrictions |
| title_full_unstemmed | Diagnostic Measures in Ridge Regression Model with AR(1) Errors under the Stochastic Linear Restrictions |
| title_short | Diagnostic Measures in Ridge Regression Model with AR(1) Errors under the Stochastic Linear Restrictions |
| title_sort | diagnostic measures in ridge regression model with ar 1 errors under the stochastic linear restrictions |
| topic | ridge regression stochastic linear rrestrictions autocorrelated error terms influential analysis mean-shift outlier model |
| url | https://jsciences.ut.ac.ir/article_64795_db39943b94dc78c3bb98470b3c5bb2e5.pdf |
| work_keys_str_mv | AT azaherzadehzaherzadeh diagnosticmeasuresinridgeregressionmodelwithar1errorsunderthestochasticlinearrestrictions AT arrasekh diagnosticmeasuresinridgeregressionmodelwithar1errorsunderthestochasticlinearrestrictions AT bbabadi diagnosticmeasuresinridgeregressionmodelwithar1errorsunderthestochasticlinearrestrictions |