The Resource A new concept for tuning design weights in survey sampling : jackknifing in theory and practice, Sarjinder Singh, Stephen Sedory, Maria Rueda, Antonio Arcos, Raghunath Arnab, (electronic book)
A new concept for tuning design weights in survey sampling : jackknifing in theory and practice, Sarjinder Singh, Stephen Sedory, Maria Rueda, Antonio Arcos, Raghunath Arnab, (electronic book)
Resource Information
The item A new concept for tuning design weights in survey sampling : jackknifing in theory and practice, Sarjinder Singh, Stephen Sedory, Maria Rueda, Antonio Arcos, Raghunath Arnab, (electronic book) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Liverpool.This item is available to borrow from 1 library branch.
Resource Information
The item A new concept for tuning design weights in survey sampling : jackknifing in theory and practice, Sarjinder Singh, Stephen Sedory, Maria Rueda, Antonio Arcos, Raghunath Arnab, (electronic book) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Liverpool.
This item is available to borrow from 1 library branch.
 Summary
 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
 Language
 eng
 Extent
 1 online resource
 Contents

 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
 Chapter 2: Tuning of jackknife estimator2.1. Introduction; 2.2. Notation; 2.3. Tuning with a chisquare 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 chisquare 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
 Chapter 3: Model assisted tuning of estimators3.1. Introduction; 3.2. Model assisted tuning with a chisquare distance function; 3.2.1. Estimation of variance and coverage; 3.2.2. R code; 3.3. Model assisted tuning with a dualtoempirical loglikelihood (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 chisquare distance; 4.3.1. Estimation of variance of the estimator of variance and coverage
 4.3.2. R code4.3.3. Remark on tuning with a chisquare distance; 4.3.4. Numerical illustration; 4.3.5. R code used for illustration; 4.3.6. Fdistribution; 4.4. Tuning of estimator of finite population variance with a dualtoempirical loglikelihood (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 chisquare 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
 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
 Isbn
 9780081005941
 Label
 A new concept for tuning design weights in survey sampling : jackknifing in theory and practice
 Title
 A new concept for tuning design weights in survey sampling
 Title remainder
 jackknifing in theory and practice
 Statement of responsibility
 Sarjinder Singh, Stephen Sedory, Maria Rueda, Antonio Arcos, Raghunath Arnab
 Language
 eng
 Summary
 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
 Cataloging source
 NLE
 http://library.link/vocab/creatorDate
 1963
 http://library.link/vocab/creatorName
 Singh, Sarjinder
 Dewey number
 001.422
 Index
 no index present
 LC call number
 QA276
 Literary form
 non fiction
 Nature of contents
 dictionaries
 http://library.link/vocab/relatedWorkOrContributorName

 Sedory, Stephen
 Rueda, Maria
 Arcos, Antonio
 Arnab, Raghunath
 http://library.link/vocab/subjectName
 Sampling (Statistics)
 Label
 A new concept for tuning design weights in survey sampling : jackknifing in theory and practice, Sarjinder Singh, Stephen Sedory, Maria Rueda, Antonio Arcos, Raghunath Arnab, (electronic book)
 Carrier category
 online resource
 Carrier category code
 cr
 Carrier MARC source
 rdacarrier
 Content category
 text
 Content type code
 txt
 Content type MARC source
 rdacontent
 Contents

 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
 Chapter 2: Tuning of jackknife estimator2.1. Introduction; 2.2. Notation; 2.3. Tuning with a chisquare 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 chisquare 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
 Chapter 3: Model assisted tuning of estimators3.1. Introduction; 3.2. Model assisted tuning with a chisquare distance function; 3.2.1. Estimation of variance and coverage; 3.2.2. R code; 3.3. Model assisted tuning with a dualtoempirical loglikelihood (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 chisquare distance; 4.3.1. Estimation of variance of the estimator of variance and coverage
 4.3.2. R code4.3.3. Remark on tuning with a chisquare distance; 4.3.4. Numerical illustration; 4.3.5. R code used for illustration; 4.3.6. Fdistribution; 4.4. Tuning of estimator of finite population variance with a dualtoempirical loglikelihood (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 chisquare 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
 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
 Control code
 SD932063208
 Extent
 1 online resource
 Form of item
 online
 Governing access note
 Owing to Legal Deposit regulations this resource may only be accessed from within National Library of Scotland. For more information contact enquiries@nls.uk.
 Isbn
 9780081005941
 Isbn Type
 (hbk)
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code
 c
 Specific material designation
 remote
 Label
 A new concept for tuning design weights in survey sampling : jackknifing in theory and practice, Sarjinder Singh, Stephen Sedory, Maria Rueda, Antonio Arcos, Raghunath Arnab, (electronic book)
 Carrier category
 online resource
 Carrier category code
 cr
 Carrier MARC source
 rdacarrier
 Content category
 text
 Content type code
 txt
 Content type MARC source
 rdacontent
 Contents

 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
 Chapter 2: Tuning of jackknife estimator2.1. Introduction; 2.2. Notation; 2.3. Tuning with a chisquare 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 chisquare 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
 Chapter 3: Model assisted tuning of estimators3.1. Introduction; 3.2. Model assisted tuning with a chisquare distance function; 3.2.1. Estimation of variance and coverage; 3.2.2. R code; 3.3. Model assisted tuning with a dualtoempirical loglikelihood (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 chisquare distance; 4.3.1. Estimation of variance of the estimator of variance and coverage
 4.3.2. R code4.3.3. Remark on tuning with a chisquare distance; 4.3.4. Numerical illustration; 4.3.5. R code used for illustration; 4.3.6. Fdistribution; 4.4. Tuning of estimator of finite population variance with a dualtoempirical loglikelihood (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 chisquare 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
 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
 Control code
 SD932063208
 Extent
 1 online resource
 Form of item
 online
 Governing access note
 Owing to Legal Deposit regulations this resource may only be accessed from within National Library of Scotland. For more information contact enquiries@nls.uk.
 Isbn
 9780081005941
 Isbn Type
 (hbk)
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code
 c
 Specific material designation
 remote
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