Secure CheckoutPersonal information is secured with SSL technology.
Free ShippingFree global shipping
No minimum order.
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.
- 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
An essential guide for early career econometricians and statisticians seeking to develop well designed, cost-effective and efficient sampling studies
- Studying the Quality of Environment Variables Using a Randomized Response Procedure for the Estimation of a Proportion Through Ranked Set Sampling
2. evelopment of a New Control Chart Based on Ranked Repetitive Sampling
3. mproved Ratio-Cum-Product Estimators of the Population Mean
4. Estimation of the Distribution Function Using Moving Extreme Ranked Set Sampling (MERSS)
5. Statistical Inference of Ranked Set Sampling Via Resampling Methods
6. Extensions of Some Randomized Response Procedures Related with Gupta-Thornton Method: The Use of Order Statistics
7. Ranked Set Sampling Estimation of the Population Mean When Information on an Attribute Is Available
8. Modified Partially Ordered Judgment Subset Sampling Schemes
9. Ranked Set Sampling With Unequal Sample Sizes
10. A New Morgenstern Type Bivariate Exponential Distribution with Known Coefficient of Variation by Ranked Set Sampling
11. Shrinkage Estimators of Scale Parameter Towards an Interval of Morgenstern Type Bivariate Uniform Distribution Using Ranked Set Sampling
12. Statistical Inference Using Stratified Ranked Set Samples From Finite Populations
13. Simultaneous Estimation of Means of Two Sensitive Variables Using Ranked Set Sampling
14. Forced Quantitative Randomized Response Model Using Ranked Set Sampling
15. Construction of Strata Boundaries for Ranked Set Sampling
16. Calibrated Estimator of Population Mean Using Two-Stage Ranked Set Sampling
17. Estimation of Population Mean Using Information on Auxiliary Attribute: A Review
18. Ratio and Product Type Exponential Estimators for Population Mean Using Ranked Set Sampling
19. Extropy Estimation in Ranked Set Sampling With its Application in Testing Uniformity
20. Selection and Estimation in Ranked Set Sampling using R
21. Variance Estimation of Persons Infected With AIDS Under Ranked Set Sampling
- No. of pages:
- © Academic Press 2018
- 16th October 2018
- Academic Press
- Paperback ISBN:
- eBook ISBN:
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.
University of Havana, Havana, Cuba
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.
Al-Bayt University, Mafraq, Jordan
Elsevier.com visitor survey
We are always looking for ways to improve customer experience on Elsevier.com.
We would like to ask you for a moment of your time to fill in a short questionnaire, at the end of your visit.
If you decide to participate, a new browser tab will open so you can complete the survey after you have completed your visit to this website.
Thanks in advance for your time.