Robust Estimators for the Correlation Measure to Resist Outliers in Data
The objective of this research was to propose a composite correlation coefficient to estimate the rank correlation coefficient of two variables. A simulation study was conducted using 228 situations for a bivariate normal distribution to compare the robustness properties of the proposed rank correla...
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| Format: | Article |
| Language: | English |
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ITB Journal Publisher
2016-12-01
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| Series: | Journal of Mathematical and Fundamental Sciences |
| Subjects: | |
| Online Access: | http://journals.itb.ac.id/index.php/jmfs/article/view/2552 |
| _version_ | 1818394933513420800 |
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| author | Juthaphorn Sinsomboonthong |
| author_facet | Juthaphorn Sinsomboonthong |
| author_sort | Juthaphorn Sinsomboonthong |
| collection | DOAJ |
| description | The objective of this research was to propose a composite correlation coefficient to estimate the rank correlation coefficient of two variables. A simulation study was conducted using 228 situations for a bivariate normal distribution to compare the robustness properties of the proposed rank correlation coefficient with three estimators, namely, Spearman’s rho, Kendall’s tau and Plantagenet’s correlation coefficients when the data were contaminated with outliers. In both cases of non-outliers and outliers in the data, it was found that the composite correlation coefficient seemed to be the most robust estimator for all sample sizes, whatever the level of the correlation coefficient. |
| first_indexed | 2024-12-14T06:09:05Z |
| format | Article |
| id | doaj.art-98d5efc093ab4e8ea6c41c0abc3d0333 |
| institution | Directory Open Access Journal |
| issn | 2337-5760 2338-5510 |
| language | English |
| last_indexed | 2024-12-14T06:09:05Z |
| publishDate | 2016-12-01 |
| publisher | ITB Journal Publisher |
| record_format | Article |
| series | Journal of Mathematical and Fundamental Sciences |
| spelling | doaj.art-98d5efc093ab4e8ea6c41c0abc3d03332022-12-21T23:14:11ZengITB Journal PublisherJournal of Mathematical and Fundamental Sciences2337-57602338-55102016-12-0148326327510.5614/j.math.fund.sci.2016.48.3.7Robust Estimators for the Correlation Measure to Resist Outliers in DataJuthaphorn SinsomboonthongThe objective of this research was to propose a composite correlation coefficient to estimate the rank correlation coefficient of two variables. A simulation study was conducted using 228 situations for a bivariate normal distribution to compare the robustness properties of the proposed rank correlation coefficient with three estimators, namely, Spearman’s rho, Kendall’s tau and Plantagenet’s correlation coefficients when the data were contaminated with outliers. In both cases of non-outliers and outliers in the data, it was found that the composite correlation coefficient seemed to be the most robust estimator for all sample sizes, whatever the level of the correlation coefficient.http://journals.itb.ac.id/index.php/jmfs/article/view/2552correlation coefficientrank correlation coefficientoutliersrobustnessestimator |
| spellingShingle | Juthaphorn Sinsomboonthong Robust Estimators for the Correlation Measure to Resist Outliers in Data Journal of Mathematical and Fundamental Sciences correlation coefficient rank correlation coefficient outliers robustness estimator |
| title | Robust Estimators for the Correlation Measure to Resist Outliers in Data |
| title_full | Robust Estimators for the Correlation Measure to Resist Outliers in Data |
| title_fullStr | Robust Estimators for the Correlation Measure to Resist Outliers in Data |
| title_full_unstemmed | Robust Estimators for the Correlation Measure to Resist Outliers in Data |
| title_short | Robust Estimators for the Correlation Measure to Resist Outliers in Data |
| title_sort | robust estimators for the correlation measure to resist outliers in data |
| topic | correlation coefficient rank correlation coefficient outliers robustness estimator |
| url | http://journals.itb.ac.id/index.php/jmfs/article/view/2552 |
| work_keys_str_mv | AT juthaphornsinsomboonthong robustestimatorsforthecorrelationmeasuretoresistoutliersindata |