A New Concept For Tuning Design Weights In Survey Sampling: Jackknifing In Theory And Practice

Hardcover | November 26, 2015

bySarjinder Singh, Stephen A. Sedory, Maria Del Mar Rueda

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A New Concept for Tuning Design Weights in Survey Sampling: Jackknifing in Theory and Practiceintroduces 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.



  • Explains how to calibrate design weights in survey sampling
  • Discusses how Jackknifing is needed in design weights in survey sampling
  • Describes how design weights are imputed in survey sampling

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From the Publisher

A New Concept for Tuning Design Weights in Survey Sampling: Jackknifing in Theory and Practiceintroduces 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 anal...

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 Met...
Format:HardcoverDimensions:316 pages, 9.41 × 7.24 × 0.98 inPublished:November 26, 2015Publisher:Academic PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0081005946

ISBN - 13:9780081005941

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Extra Content

Table of Contents

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