Auxiliary data needs to be incorporated into survey sampling in order to create a precise
population parameter estimator. This study investigates improving the efficiency of these …

Values that are too large or small enough can be found in many data sets. Therefore, the
estimator can yield ambiguous findings if several of the incredible deals are picked for the …

With an emphasis on memory-type approaches, this study presents a class of estimators
specifically designed for estimating population variation in simple random sampling (SRS) …

In modern age of information technology, data is available everywhere in huge amount.
Every sector generates lot of data every day. The investigation of each unit of data is not …

In this paper, we propose a generalized class of exponential‐type estimators for estimating
the finite population distribution function using dual auxiliary variables under stratified …

Recently, several memory-type mean estimators (including ratio, product, and logarithmic)
have been developed. These estimators rely on exponentially weighted moving average …

In general, the incorporation of supplementary information reduces the Mean Square Error
(MSE) and, consequently, enhances the precision of estimating a population parameter …

In the contemporary era of information technology, copious amounts of data are ubiquitous,
generated across various sectors on a daily basis. Analyzing every unit of data is impractical …

This paper aims to investigate the impact of transformed auxiliary variables on the
performance of variance estimators of finite population under adaptive cluster sampling …

In this paper, we propose an efficient estimator for the estimation of population mean using
the information of the two auxiliary attributes under stratified random sampling. The bias …