|
|
 |
| |
|
|
|
Generalized log type estimator of population mean in Adaptive cluster sampling |
|
|
|
PP: 73-79 |
|
|
|
Author(s) |
|
|
|
Rajesh Singh,
Prayas Sharma,
Rohan Mishra,
|
|
|
|
Abstract |
|
|
| The use of functions like log and exponential in developing highly efficient estimators has been extensively studied in traditional sampling designs. Such estimators have proven to be more efficient in some studies but they cannot be used when the population under study is patchy or hidden clustered since in such situations estimators developed under the Adaptive cluster sampling design are generally used. Thus, in this paper, we have proposed a generalized log type class of estimators of population mean in the Adaptive cluster sampling design and studied various new log type estimators developed from the proposed class. The derivations of properties like bias and MSE have been presented up to the first order of approximations. To show the novelty of the new developed log type estimators over several competing estimators considered in this paper various simulation studies have been conducted. Results show that the new developed log type estimators perform better.
|
|
|
|
|
|
|
|
