Abstract
This article concerns entropy estimation using judgment post stratification sampling. Some nonparametric estimators are developed and shown to be consistent. Monte Carlo simulations are used to compare these estimators with their competitors in simple random sampling. The results indicate the preference of the new estimators.
Highlights
Judgement post stratification (JPS) sampling scheme, introduced by MacEachern et al (2004), has wide applications in situations where auxiliary information is available to induce an additional ranking structure in simple random sampling (SRS) scheme
We developed some nonparametric entropy estimators for judgement post stratification sampling scheme
The estimators were obtained by using different cumulative distribution function estimators in the JPS setting
Summary
Judgement post stratification (JPS) sampling scheme, introduced by MacEachern et al (2004), has wide applications in situations where auxiliary information is available to induce an additional ranking structure in simple random sampling (SRS) scheme. A judgement post stratified sample can still be analyzed with standard SRS procedures This is very useful in situations in which the researcher believes that the ranking process is too poor or the required statistical method has not been developed yet for the JPS setting. Both RSS and JPS sampling schemes are useful in situations in which exact measurement of sample units is expensive or time-consuming but ranking them (without obtaining their precise values) is easy and cheap These situations frequently happen in forestry (Halls and Dell, 1966), medicine (Chen et al, 2005), environmental monitoring (Kvam, 2003; Nussbaum and Sinha, 1997; and Ozturk et al, 2005), reliability (Mahdizadeh and Zamanzade, 2016) and entomology (Howard et al, 1982).
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Pakistan Journal of Statistics and Operation Research
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
