Switch to
| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
24
|
| pubmed:dateCreated |
1979-12-20
|
| pubmed:abstractText |
Finite population estimation problems are formulated as prediction problems under superpopulation models. For linear regression models, a general theorem on optimal linear estimation is presented. The theorem is applied to simple cross-classification models to generate and analyze various statistics for estimating small area totals. These statistics include the synthetic and composite estimators, as well as some interesting alternatives.
|
| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:citationSubset |
IM
|
| pubmed:status |
MEDLINE
|
| pubmed:month |
Feb
|
| pubmed:issn |
1046-9516
|
| pubmed:author | |
| pubmed:issnType |
Print
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
63-87
|
| pubmed:dateRevised |
2007-11-15
|
| pubmed:meshHeading | |
| pubmed:year |
1979
|
| pubmed:articleTitle |
Prediction models in small area estimation.
|
| pubmed:publicationType |
Journal Article
|