Abstract
The efficiency of Double Ranked Set Sampling (DRSS) suggested by Al-Saleh and Al- Kadiri (2000) as a modification of the Ranked Set Sampling (RSS) depends largely on the success in ranking the variable of interest. With large sample size, it becomes more difficult to apply in real life situations. With this, we introduce Median Double Ranked Set Sampling (MDRSS), Double Median Ranked Set Sampling (DMRSS) and Extreme Double Ranked Set Sampling (EDRSS), which might be used in some areas of applications instead of DRSS to increase the efficiency of the estimators. It is shown that the new estimators for the population mean are unbiased estimator if the underlying distribution is symmetric and more efficient than RSS and DRSS for most of the distributions considered in this study.
| Original language | English |
|---|---|
| Title of host publication | Progress in Applied Statistics Research |
| Publisher | Nova Science Publishers, Inc. |
| Pages | 245-260 |
| Number of pages | 16 |
| ISBN (Electronic) | 9781617286643 |
| ISBN (Print) | 9781604561241 |
| State | Published - 7 Aug 2009 |
Bibliographical note
Publisher Copyright:© 2009 Nova Science Publishers, Inc.
Keywords
- And simple random sampling
- Double median ranked set sampling
- Double ranked set sampling
- Extreme double ranked set sampling
- Extreme ranked set sampling
- Median double ranked set sampling
- Median ranked set sampling
- Ranked set sampling
- Relative efficiency
ASJC Scopus subject areas
- General Mathematics