Winsorized and Smoothed Estimation of the Location Model in Mixed Variables Discrimination
View references (45)The location model is a familiar basis and excellent tool for discriminant analysis of mixtures of categorical and continuous variables compared to other existing discrimination methods.However, the presence of outliers affects the estimation of population parameters, hence causi...
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| Format: | Article |
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Natural Sciences Publishing USA
2018
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| _version_ | 1803628719887089664 |
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| author | Hamid, Hashibah |
| author_facet | Hamid, Hashibah |
| author_sort | Hamid, Hashibah |
| collection | UUM |
| description | View references (45)The location model is a familiar basis and excellent tool for discriminant analysis of mixtures of categorical and continuous variables compared to other existing discrimination methods.However, the presence of outliers affects the estimation of population parameters, hence causing the inability of the location model to provide accurate statistical model and interpretation as well.In this paper, we construct a new location model through the integration of Winsorization and smoothing approach taking into account mixed variables in the presence of outliers.The newly constructed model successfully enhanced the model performance compared to the earlier developed location models. The results of analysis proved that this new location model can be used as an alternative method for discrimination tasks as for academicians and practitioners in future applications, especially when they encountered outliers problem and had some empty cells in the data sample. |
| first_indexed | 2024-07-04T06:26:26Z |
| format | Article |
| id | uum-24428 |
| institution | Universiti Utara Malaysia |
| last_indexed | 2024-07-04T06:26:26Z |
| publishDate | 2018 |
| publisher | Natural Sciences Publishing USA |
| record_format | dspace |
| spelling | uum-244282018-07-23T01:10:00Z https://repo.uum.edu.my/id/eprint/24428/ Winsorized and Smoothed Estimation of the Location Model in Mixed Variables Discrimination Hamid, Hashibah QA75 Electronic computers. Computer science View references (45)The location model is a familiar basis and excellent tool for discriminant analysis of mixtures of categorical and continuous variables compared to other existing discrimination methods.However, the presence of outliers affects the estimation of population parameters, hence causing the inability of the location model to provide accurate statistical model and interpretation as well.In this paper, we construct a new location model through the integration of Winsorization and smoothing approach taking into account mixed variables in the presence of outliers.The newly constructed model successfully enhanced the model performance compared to the earlier developed location models. The results of analysis proved that this new location model can be used as an alternative method for discrimination tasks as for academicians and practitioners in future applications, especially when they encountered outliers problem and had some empty cells in the data sample. Natural Sciences Publishing USA 2018 Article PeerReviewed Hamid, Hashibah (2018) Winsorized and Smoothed Estimation of the Location Model in Mixed Variables Discrimination. Applied Mathematics & Information Sciences, 12 (1). pp. 133-138. ISSN 1935-0090 http://doi.org/10.18576/amis/120112 doi:10.18576/amis/120112 doi:10.18576/amis/120112 |
| spellingShingle | QA75 Electronic computers. Computer science Hamid, Hashibah Winsorized and Smoothed Estimation of the Location Model in Mixed Variables Discrimination |
| title | Winsorized and Smoothed Estimation of the Location Model in Mixed Variables Discrimination |
| title_full | Winsorized and Smoothed Estimation of the Location Model in Mixed Variables Discrimination |
| title_fullStr | Winsorized and Smoothed Estimation of the Location Model in Mixed Variables Discrimination |
| title_full_unstemmed | Winsorized and Smoothed Estimation of the Location Model in Mixed Variables Discrimination |
| title_short | Winsorized and Smoothed Estimation of the Location Model in Mixed Variables Discrimination |
| title_sort | winsorized and smoothed estimation of the location model in mixed variables discrimination |
| topic | QA75 Electronic computers. Computer science |
| work_keys_str_mv | AT hamidhashibah winsorizedandsmoothedestimationofthelocationmodelinmixedvariablesdiscrimination |