Robust Nonparametric Methods
The nonparametric procedures for simple location problems offer the user highly efficient and robust methods and form an attractive alternative to traditional least squares (LS) procedures. Hettmanspeger et al examine examine nonparametric methods.
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| Veröffentlicht in: | Journal of the American Statistical Association 2000-12, Vol.95 (452), p.1308-1312 |
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| container_title | Journal of the American Statistical Association |
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| creator | Hettmansperger, Thomas P. McKean, Joseph W. Sheather, Simon J. |
| description | The nonparametric procedures for simple location problems offer the user highly efficient and robust methods and form an attractive alternative to traditional least squares (LS) procedures. Hettmanspeger et al examine examine nonparametric methods. |
| doi_str_mv | 10.1080/01621459.2000.10474337 |
| format | Article |
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| identifier | ISSN: 0162-1459 |
| ispartof | Journal of the American Statistical Association, 2000-12, Vol.95 (452), p.1308-1312 |
| issn | 0162-1459 1537-274X |
| language | eng |
| recordid | cdi_proquest_miscellaneous_38998447 |
| source | Periodicals Index Online; JSTOR Mathematics & Statistics; JSTOR Archive Collection A-Z Listing; Taylor & Francis:Master (3349 titles) |
| subjects | Applied statistics Datasets Economic models Estimators Linear models Linear regression Mathematical economics Modelling Nonparametric methods Outliers Point estimators Preliminary estimates Rank tests Statistical methods Statistics Vignettes for the Year 2000: Theory and Methods |
| title | Robust Nonparametric Methods |
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