Estimation in Complex Sampling Designs Based on Resampling Methods

Bardia Panahbehagh ()
Additional contact information
Bardia Panahbehagh: Kharazmi University

Journal of Agricultural, Biological and Environmental Statistics, 2020, vol. 25, issue 2, No 5, 206-228

Abstract: Abstract Generally, to select a representative sample of the population, we use a combination of several probabilistic sampling methods which is called a complex sampling design. A complex sampling design usually needs very sophisticated mathematical calculations to provide unbiased estimators of the population parameters. Therefore, only a limited number of sampling designs are commonly used in practice. In the present study, to overcome this complexity, we propose a general method of estimation based on resampling that is suitable for all standard designs, either conventional or adaptive. In this method, we calculate Murthy estimator as an unbiased estimator for the population mean and its variance estimator without intensive mathematical calculations. Using this method, researchers can perform any probability design with the guarantee that the estimator is unbiased. To show this ability and as an application of the method, we introduce Adaptive Random Walk Sampling as a complex and efficient sampling design, proper for the quadrat-based environmental population. Despite the complexity of this design, the method proposed in this paper provides unbiased estimator for the population mean based on the design and then makes it a practical design. Simulations confirm the expected performance of the method.

Keywords: Complex designs; Adaptive designs; Unbiased estimators; Murthy estimator; Monte Carlo resampling methods (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s13253-020-00390-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jagbes:v:25:y:2020:i:2:d:10.1007_s13253-020-00390-7

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/13253

DOI: 10.1007/s13253-020-00390-7

Access Statistics for this article

Journal of Agricultural, Biological and Environmental Statistics is currently edited by Stephen Buckland

More articles in Journal of Agricultural, Biological and Environmental Statistics from Springer, The International Biometric Society, American Statistical Association
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().