Ranked Set Sampling Models and Methods
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| Title: | Ranked Set Sampling Models and Methods |
|---|---|
| Description: | When it comes to data collection and analysis, ranked set sampling (RSS) continues to increasingly be the focus of methodological research. This type of sampling is an alternative to simple random sampling and can offer substantial improvements in precision and efficient estimation. There are different methods within RSS that can be further explored and discussed. On top of being efficient, RSS is cost-efficient and can be used in situations where sample units are difficult to obtain. With new results in modeling and applications, and a growing importance in theory and practice, it is essential for modeling to be further explored and developed through research. Ranked Set Sampling Models and Methods presents an innovative look at modeling survey sampling research and new models of RSS along with the future potentials of it. The book provides a panoramic view of the state of the art of RSS by presenting some previously known and new models. The chapters illustrate how the modeling is to be developed and how they improve the efficiency of the inferences. The chapters highlight topics such as bootstrap methods, fuzzy weight ranked set sampling method, item count technique, stratified ranked set sampling, and more. This book is essential for statisticians, social and natural science scientists, physicians and all the persons involved with the use of sampling theory in their research along with practitioners, researchers, academicians, and students interested in the latest models and methods for ranked set sampling. |
| Authors: | Carlos N. Bouza-Herrera |
| Resource Type: | eBook. |
| Subjects: | Sampling (Statistics), Ranking and selection (Statistics) |
| Categories: | COMPUTERS / Database Administration & Management, COMPUTERS / General, COMPUTERS / Data Science / General |
| Database: | eBook Academic Collection (EBSCOhost) |
| FullText | Links: – Type: ebook-pdf – Type: ebook-epub Text: Availability: 0 |
|---|---|
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| Items | – Name: Title Label: Title Group: Ti Data: Ranked Set Sampling Models and Methods – Name: Abstract Label: Description Group: Ab Data: When it comes to data collection and analysis, ranked set sampling (RSS) continues to increasingly be the focus of methodological research. This type of sampling is an alternative to simple random sampling and can offer substantial improvements in precision and efficient estimation. There are different methods within RSS that can be further explored and discussed. On top of being efficient, RSS is cost-efficient and can be used in situations where sample units are difficult to obtain. With new results in modeling and applications, and a growing importance in theory and practice, it is essential for modeling to be further explored and developed through research. Ranked Set Sampling Models and Methods presents an innovative look at modeling survey sampling research and new models of RSS along with the future potentials of it. The book provides a panoramic view of the state of the art of RSS by presenting some previously known and new models. The chapters illustrate how the modeling is to be developed and how they improve the efficiency of the inferences. The chapters highlight topics such as bootstrap methods, fuzzy weight ranked set sampling method, item count technique, stratified ranked set sampling, and more. This book is essential for statisticians, social and natural science scientists, physicians and all the persons involved with the use of sampling theory in their research along with practitioners, researchers, academicians, and students interested in the latest models and methods for ranked set sampling. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Carlos+N%2E+Bouza-Herrera%22">Carlos N. Bouza-Herrera</searchLink> – Name: TypePub Label: Resource Type Group: TypPub Data: eBook. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Sampling+%28Statistics%29%22">Sampling (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Ranking+and+selection+%28Statistics%29%22">Ranking and selection (Statistics)</searchLink> – Name: SubjectBISAC Label: Categories Group: Su Data: <searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Database+Administration+%26+Management%22">COMPUTERS / Database Administration & Management</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+General%22">COMPUTERS / General</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Data+Science+%2F+General%22">COMPUTERS / Data Science / General</searchLink> |
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| RecordInfo | BibRecord: BibEntity: Classifications: – Code: 519.52 Scheme: ddc Type: prePub Languages: – Code: eng Text: English Subjects: – SubjectFull: Sampling (Statistics) Type: general – SubjectFull: Ranking and selection (Statistics) Type: general Titles: – TitleFull: Ranked Set Sampling Models and Methods Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Carlos N. Bouza-Herrera – PersonEntity: Name: NameFull: Carlos N. Bouza-Herrera IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2022 – D: 04 M: 01 Type: profile Y: 2022 Identifiers: – Type: isbn-print Value: 9781799875567 – Type: isbn-electronic Value: 9781799875581 – Type: isbn-electronic Value: 9781799875598 Titles: – TitleFull: Ranked Set Sampling Models and Methods Type: main |
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