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.
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.
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Autorenporträt
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.
Inhaltsangabe
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
