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Ranked Set Sampling

65 Years Improving the Accuracy in Data Gathering

  • 1st Edition - October 16, 2018
  • Latest edition
  • Authors: Carlos N. Bouza-Herrera, Amer Ibrahim Falah Al-Omari
  • Language: English

Ranked Set Sampling: 65 Years Improving the Accuracy in Data Gathering is an advanced survey technique which seeks to improve the likelihood that collected sample data presents a… Read more

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Description

Ranked Set Sampling: 65 Years Improving the Accuracy in Data Gathering is an advanced survey technique which seeks to improve the likelihood that collected sample data presents a good representation of the population and minimizes the costs associated with obtaining them. The main focus of many agricultural, ecological and environmental studies is the development of well designed, cost-effective and efficient sampling designs, giving RSS techniques a particular place in resolving the disciplinary problems of economists in application contexts, particularly experimental economics. This book seeks to place RSS at the heart of economic study designs.

Key features

  • Focuses on how researchers should manipulate RSS techniques for specific applications
  • Discusses RSS performs in popular statistical models, such as regression and hypothesis testing
  • Includes a discussion of open theoretical research problems
  • Provides mathematical proofs, enabling researchers to develop new models

Readership

An essential guide for early career econometricians and statisticians seeking to develop well designed, cost-effective and efficient sampling studies

Table of contents

1. Studying the Quality of Environment Variables Using a Randomized Response Procedure for the Estimation of a Proportion Through Ranked Set Sampling2. evelopment of a New Control Chart Based on Ranked Repetitive Sampling3. mproved Ratio-Cum-Product Estimators of the Population Mean4. Estimation of the Distribution Function Using Moving Extreme Ranked Set Sampling (MERSS)5. Statistical Inference of Ranked Set Sampling Via Resampling Methods6. Extensions of Some Randomized Response Procedures Related with Gupta-Thornton Method: The Use of Order Statistics7. Ranked Set Sampling Estimation of the Population Mean When Information on an Attribute Is Available8. Modified Partially Ordered Judgment Subset Sampling Schemes9. Ranked Set Sampling With Unequal Sample Sizes10. A New Morgenstern Type Bivariate Exponential Distribution with Known Coefficient of Variation by Ranked Set Sampling11. Shrinkage Estimators of Scale Parameter Towards an Interval of Morgenstern Type Bivariate Uniform Distribution Using Ranked Set Sampling12. Statistical Inference Using Stratified Ranked Set Samples From Finite Populations13. Simultaneous Estimation of Means of Two Sensitive Variables Using Ranked Set Sampling14. Forced Quantitative Randomized Response Model Using Ranked Set Sampling15. Construction of Strata Boundaries for Ranked Set Sampling16. Calibrated Estimator of Population Mean Using Two-Stage Ranked Set Sampling17. Estimation of Population Mean Using Information on Auxiliary Attribute: A Review18. Ratio and Product Type Exponential Estimators for Population Mean Using Ranked Set Sampling19. Extropy Estimation in Ranked Set Sampling With its Application in Testing Uniformity20. Selection and Estimation in Ranked Set Sampling using R21. Variance Estimation of Persons Infected With AIDS Under Ranked Set Sampling

Product details

  • Edition: 1
  • Latest edition
  • Published: October 19, 2018
  • Language: English

About the authors

CB

Carlos N. Bouza-Herrera

Prof. Dr. Carlos Bouza-Herrera is Professor of Mathematics, Economics and Computation at Universidad de la Habana, Cuba. Herrera has headed more than 60 research projects and published more than 200 papers. His main area of investigation is in mathematical statistics. He has been author, coauthor or editor of 19 books. He is the consulting editor of Current Index to Statistics and International Abstracts of Operations Research.
Affiliations and expertise
University of Havana, Havana, Cuba

AF

Amer Ibrahim Falah Al-Omari

Professor Amer Al-Omari is a Professor of Statistics at the Department of Mathematics, and Vice-Dean of Academic Research at Al al-Bayt University, Mafraq, Jordan. He is interested in ranked set sampling, entropy, missing data, order statistics, acceptance sampling plans, and statistical inference. He has published over 100 articles.
Affiliations and expertise
Al-Bayt University, Mafraq, Jordan

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