The use of auxiliary information in the linear least-squares prediction approach to cluster sampling in a finite population
| dc.contributor.author | Madden, Ragan Burt | en |
| dc.contributor.department | Statistics | en |
| dc.contributor.department | Statistics | en |
| dc.date.accessioned | 2019-01-31T19:03:51Z | en |
| dc.date.available | 2019-01-31T19:03:51Z | en |
| dc.date.issued | 1976 | en |
| dc.description.abstract | Linear least-squares prediction methods are applied to cluster (two-stage) sampling problems in a finite population where auxiliary information is available. Two regression models which describe the behavior of the second-stage units and which utilize the auxiliary information are considered. For one model the optimum estimator of the total of the second-stage units and its mean square error (m.s.e.) are derived. The selection of clusters which minimize the m.s.e. are determined for certain cases. For both models a conventional estimator of the total is analyzed in the prediction theory framework. Optimum sampling designs for the conventional estimator are obtained for certain parameter configurations. A computer implemented study to compare the performances of the estimators for a wide range of parameter values is done. A practical problem is analyzed. | en |
| dc.description.degree | Ph. D. | en |
| dc.format.extent | ix, 180 pages, 1 unnumbered leaves | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.uri | http://hdl.handle.net/10919/87316 | en |
| dc.language.iso | en | en |
| dc.publisher | Virginia Polytechnic Institute and State University | en |
| dc.relation.isformatof | OCLC# 40194785 | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject.lcc | LD5655.V856 1976.M335 | en |
| dc.title | The use of auxiliary information in the linear least-squares prediction approach to cluster sampling in a finite population | en |
| dc.type | Dissertation | en |
| dc.type.dcmitype | Text | en |
| thesis.degree.discipline | Statistics | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Ph. D. | en |
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