Nonparametric regression method for estimating the error variance in unistage sampling
| dc.contributor.author | Otieno, Romanus Odhiambo | |
| dc.contributor.author | Mwalili, Tobias Mbithi | |
| dc.date.accessioned | 2015-06-02T12:51:36Z | |
| dc.date.available | 2015-06-02T12:51:36Z | |
| dc.date.issued | 2000 | |
| dc.description | Research Article | en_US |
| dc.description.abstract | Nonparametric regression provides computationally intensive estimation of unknown finite population quantities. Such estimation can be more robust than inference tied to model based inference. A nonparametric procedure for estimating error variance is suggested. An empirical example is given to illustrate the performance of the derived estimator vis-a-vis the currently popular variance estimator in model based surveys. | en_US |
| dc.description.sponsorship | Kenyatta University | en_US |
| dc.identifier.citation | East African Journal of Science 2(2): 107-112 (2000) | en_US |
| dc.identifier.issn | 1029-3221 | |
| dc.identifier.uri | http://ir-library.ku.ac.ke/handle/123456789/12742 | |
| dc.language.iso | en | en_US |
| dc.publisher | Faculty of Science Kenyatta University | en_US |
| dc.subject | Auxiliary variable | en_US |
| dc.subject | bandwidth | en_US |
| dc.subject | kernel estimator | en_US |
| dc.subject | ratio estimator | en_US |
| dc.subject | non-parametric regression | en_US |
| dc.subject | variance estimation | en_US |
| dc.title | Nonparametric regression method for estimating the error variance in unistage sampling | en_US |
| dc.type | Article | en_US |
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