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A new concept for tuning design weights in survey sampling : jackknifing in theory and practice /
A New Concept for Tuning Design Weights in Survey Sampling: Jackknifing in Theory and Practice introduces the new concept of tuning design weights in survey sampling by presenting three concepts: calibration, jackknifing, and imputing where needed. This new methodology allows survey statisticians to...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Amsterdam :
Academic Press,
2015.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 050 | 4 | |a QA276 | |
| 082 | 0 | 4 | |a 001.422 |2 23 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Singh, Sarjinder, |d 1963- |e author. |1 https://id.oclc.org/worldcat/entity/E39PCjxCtGR9dHVYPm7W38cMKb | |
| 245 | 1 | 2 | |a A new concept for tuning design weights in survey sampling : |b jackknifing in theory and practice / |c Sarjinder Singh, Stephen Sedory, Maria del Mar Rueda, Antonio Arcos, Raghunath Arnab. |
| 264 | 1 | |a Amsterdam : |b Academic Press, |c 2015. | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
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| 505 | 0 | |a Front Cover; A New Concept for Tuning Design Weights in Survey Sampling: Jackknifing in Theory and Practice; Copyright; Dedication; Contents; Preface; Further studies; Acknowledgments; Chapter 1: Problem of estimation; 1.1. Introduction; 1.2. Estimation problem and notation; 1.3. Modeling of jumbo pumpkins; 1.3.1. R code; 1.4. The concept of jackknifing; 1.5. Jackknifing the sample mean; 1.6. Doubly jackknifed sample mean; 1.7. Jackknifing a sample proportion; 1.8. Jackknifing of a double suffix variable sum; 1.9. Frequently asked questions; 1.10. Exercises. | |
| 505 | 8 | |a Chapter 2: Tuning of jackknife estimator2.1. Introduction; 2.2. Notation; 2.3. Tuning with a chi-square type distance function; 2.3.1. Problem of undercoverage; 2.3.2. Estimation of variance and coverage; 2.3.3. R code; 2.3.4. Remark on tuning with a chi-square distance; 2.3.5. Numerical illustration; 2.3.6. R code used for illustration; 2.3.7. Problem of negative weights; 2.4. Tuning with dell function; 2.4.1. Estimation of variance and coverage; 2.4.2. R code; 2.4.3. Numerical illustration; 2.4.4. R code used for illustration; 2.5. An important remark; 2.6. Exercises. | |
| 505 | 8 | |a Chapter 3: Model assisted tuning of estimators3.1. Introduction; 3.2. Model assisted tuning with a chi-square distance function; 3.2.1. Estimation of variance and coverage; 3.2.2. R code; 3.3. Model assisted tuning with a dual-to-empirical log-likelihood (dell) function; 3.3.1. Estimation of variance and coverage; 3.3.2. R code; 3.4. Exercises; Chapter 4: Tuned estimators of finite population variance; 4.1. Introduction; 4.2. Tuned estimator of finite population variance; 4.3. Tuning with a chi-square distance; 4.3.1. Estimation of variance of the estimator of variance and coverage. | |
| 505 | 8 | |a 4.3.2. R code4.3.3. Remark on tuning with a chi-square distance; 4.3.4. Numerical illustration; 4.3.5. R code used for illustration; 4.3.6. F-distribution; 4.4. Tuning of estimator of finite population variance with a dual-to-empirical log-likelihood (dell) function; 4.4.1. Estimation of variance and coverage; 4.4.2. R code; 4.4.3. Numerical illustration; 4.4.4. R code used for illustration; 4.5. Alternative tuning with a chi-square distance; 4.5.1. Estimation of variance and coverage; 4.5.2. R code; 4.5.3. Numerical illustration; 4.5.4. R code used for illustration. | |
| 505 | 8 | |a 4.6. Alternative tuning with a dell function4.6.1. Estimation of variance and coverage; 4.6.2. R code; 4.6.3. Numerical illustration; 4.6.4. R code used for illustration; 4.7. Exercises; Chapter 5: Tuned estimators of correlation coefficient; 5.1. Introduction; 5.2. Correlation coefficient; 5.3. Tuned estimator of correlation coefficient; 5.3.1. Estimation of variance of the estimator of correlation coefficient and coverage; 5.3.2. R code; 5.3.3. Numerical illustration; 5.3.4. R code used for illustration; 5.4. Exercises; Chapter 6: Tuning of multicharacter survey estimators. | |
| 520 | |a A New Concept for Tuning Design Weights in Survey Sampling: Jackknifing in Theory and Practice introduces the new concept of tuning design weights in survey sampling by presenting three concepts: calibration, jackknifing, and imputing where needed. This new methodology allows survey statisticians to develop statistical software for analyzing data in a more precisely and friendly way than with existing techniques. | ||
| 504 | |a Includes bibliographical references and indexes. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Sampling (Statistics) | |
| 650 | 6 | |a Échantillonnage (Statistique) | |
| 650 | 7 | |a Sampling (Statistics) |2 fast | |
| 700 | 1 | |a Sedory, Stephen A., |d 1950- |e author. |1 https://id.oclc.org/worldcat/entity/E39PCjDX66hgkhDbFKPgDKXprm | |
| 700 | 1 | |a Rueda García, Maria del Mar, |e author. | |
| 700 | 1 | |a Arcos Cebrián, Antonio, |e author. | |
| 700 | 1 | |a Arnab, Raghunath, |e author. | |
| 758 | |i has work: |a A new concept for tuning design weights in survey sampling (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGfqb6jHhh4fxTC7WgxgPP |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |z 9780081005941 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=4097056 |z Texto completo |
| 936 | |a BATCHLOAD | ||
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL4097056 | ||
| 994 | |a 92 |b IZTAP | ||