
A New Concept for Tuning Design Weights in Survey Sampling
Jackknifing in Theory and Practice
Academic Press
Published on 11. November 2015
Book
Hardback
316 pages
978-0-08-100594-1 (ISBN)
Description
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.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Elsevier Science & Technology
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 229 mm
Width: 152 mm
Weight
460 gr
ISBN-13
978-0-08-100594-1 (9780081005941)
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Schweitzer Classification
Other editions
Additional editions

Sarjinder Singh | Stephen A. Sedory | Maria Del Mar Rueda
A New Concept for Tuning Design Weights in Survey Sampling
Jackknifing in Theory and Practice
E-Book
11/2015
Academic Press
€108.00
Available for download
Persons
Sarjinder Singh has a Ph.D. degree in statistics specializing in the field of survey sampling. Associate professor of mathematics and statistics, Texas A&M University - Kingsville (h index 11). He is a founder of higher order calibration technique in survey sampling. His first paper on this topic was published in the journal Survey Methodology, Statistics Canada, during 1998. Later he published numerous papers on calibration technique, and this monograph is also based on calibration techniques but with a different aspect. He is also pioneer founder of a dual problem of calibration published in highly respectable journal Statistics-A Journal of Theoretical and Applied Statistics. He also introduced the pioneering idea of calibration using displacement function and published in an prestigious journal, Metrika. He has published over 150 research papers in the field of survey sampling. Stephen A. Sedory has a Ph.D. degree in Mathematics, and has over 20 years of teaching and research experience at graduate and undergraduate level (Associate Professor of Mathematics, Department of Mathematics, Texas A&M University-Kingsville. Although his previous work is in the field of Topology, he has recently been working in the field of survey sampling. He has introduced the idea of two-step calibration and calibrated maximum likelihood calibration weights jointly with the first author. Maria Del Mar Rueda is a full-Professor and Director of a research group focusing on design and analysis of sample surveys at the University of Granada, Spain. Antonio Arcos is an Assistant Professor of Statistics, University of Granada, Spain, and is also working in the same areas of survey sampling. Together with Maria, Antonio is not only an expert in survey sampling, but also in writing codes in R language. All R-codes in this monographs are written by Maria and Antonio. In addition, both have contributed several papers on the calibration technique in survey sampling. Raghunath Arnab has a Ph.D. in statistics with specialization in survey sampling from the Indian Statistical Institute. He is based at the Dept of Statistics, University of Botswana. He has published very good quality papers in the field of complex survey sampling. His major contribution in this monograph is to check all the theoretical derivations of the results.
Author
Texas A&M University - Kingsville, USA
Associate Professor of Mathematics, Department of Mathematics, Texas A&M University-Kingsville, USA
University of Granada, Spain
Assistant Professor of Statistics, University of Granada, Spain
Dept of Statistics, University of Botswana, Botswana
Content
1 Problem of Estimation
2 Tuning of Jackknife Estimator
3 Model Assisted Tuning of Estimators
4 Tuned Estimators of Finite Population Variance
5 Tuned Estimators of Finite Population Correlation Coefficient
6 Tuning of Multi-Character Survey Estimators
7 Tuning of the Horvitz-Thompson Estimator
8 Tuning in Stratified Sampling
9 Tuning using Multiauxiliary Information
10 A Brief Review of Related Work
Bibliography
Handy Subject Index
Author Index
2 Tuning of Jackknife Estimator
3 Model Assisted Tuning of Estimators
4 Tuned Estimators of Finite Population Variance
5 Tuned Estimators of Finite Population Correlation Coefficient
6 Tuning of Multi-Character Survey Estimators
7 Tuning of the Horvitz-Thompson Estimator
8 Tuning in Stratified Sampling
9 Tuning using Multiauxiliary Information
10 A Brief Review of Related Work
Bibliography
Handy Subject Index
Author Index