Double-sampling regression-cum-exponential estimator of the mean of a sensitive variable

Saleem, Iram; Sanaullah, Aamir; Hanif, Muhammad

doi:10.1080/08898480.2019.1565273

Cited by 18 publications

(4 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This empirical research also demonstrated that the expertise of the projected mean of geometric proportion estimation and the newly introduced estimator of proportion are similar but with lesser biases. Saleem et al (2019) utilized double sampling types to estimate the variable's mean with sensitive features. They also suggested the arithmetical expressions of biases and MSE and conducted a numerical study to conclude the capability of the predictable estimator.…”

Section: Literaturementioning

confidence: 99%

Median estimation in the presence of non-response using randomised response technique

Hussain,

Mahmood,

Mahmood

et al. 2023

Nat. App. Sci. Int. J.

View full text Add to dashboard Cite

The theory of parameter estimation was developed a long time ago and is currently a widely accepted scientific approach. In some situations where the mean has to deal with the effect of extreme values, the median can be used instead. As there is almost little literature available on median estimation in the existence of non-responsive with the help of the Randomized Response Technique (RRT), the main objective of this paper was to develop a basic theoretical framework for median estimation in the existence of non-responsive with the help of RRT. In this work, we suggested median estimation for delicate variables in auxiliary information using a randomised response model. We have suggested a basic median estimator, product, ratio, exponential product, exponential ratio, and regression cum ratio estimation of the median for non-response by utilising RRT. The mathematical derivations for optimum values of constants, biasness, and Mean Square Error (MSE) of purposed estimators result from the application of well-known Taylor and exponential expansions. The performance of mentioned estimators is evaluated through the numerical study of two populations which discovered the regression cum ratio estimate is more proficient than the remaining estimations mentioned in this article.

show abstract

Section: Literaturementioning

confidence: 99%

Median estimation in the presence of non-response using randomised response technique

Hussain,

Mahmood,

Mahmood

et al. 2023

Nat. App. Sci. Int. J.

View full text Add to dashboard Cite

show abstract

“…Sousa et al [5]. Gupta et al [6], Koyuncu et al [7], Sanaullah et al [8], Saleem et al [9] and Sanaullah et al [10] presented mean estimators to estimate the population mean based on randomized response technique. Mushtaq et al [11] introduced ratio, regression and general class of estimators for the estimation of population mean using non-sensitive variable under stratified random sampling.…”

Section: Original Research Articlementioning

confidence: 99%

Development of Estimation Procedure of Population Variance in Stratified Randomized Response Technique

Mushtaq¹,

Saleem²

2020

AJPAS

Self Cite

View full text Add to dashboard Cite

Singh et al. (2016) presented a ratio and regression estimators of population variance of a sensitive variable using auxiliary information based on randomized response technique (RRT). In this article, the RRT is considered in stratified random sampling for the estimation of variance. A generalized class of estimators of variance in stratified RRT is proposed and derive the procedure of variance estimation in stratified RRT. The expression of the bias and mean square error are expressed. The empirical findings support the soundness of proposed scheme of variance estimation.

show abstract

“…In the case of nonresponse using RRT under two-phase sampling, Sanaullah et al [17] proposed a generalized family of estimators for the nite population mean of a susceptible research variable. Quantitative scrambled randomised response models are considerably improved by Saleem et al [18] by assessing the performance of the population mean estimator. Waseem et al [19] presented a generalized exponential type estimator for the mean of a sensitive variable using information from a nonsensitive auxiliary variable.…”

Section: Introductionmentioning

confidence: 99%

Generalized Difference-Cum Exponential Class of Estimators for Estimating Population Parameters of the Sensitive Variable

Vishwakarma

Yadav

Bari

2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

We propose a generalized class of estimators to estimate general population parameters of susceptible research variables using additional auxiliary information in SRSWOR. The population constants such as the coefficient of variation, the population mean, the standard deviation, and the population mean square are defined using a conventional estimator. The expression for the mean square errors of the proposed class is derived up to the first order of approximation. To compare the effectiveness of the proposed class of estimators, an empirical study is conducted utilizing real and simulated data sets. Theoretical and empirical research demonstrates that the suggested generalized class of estimators outperforms other current estimators.

show abstract

Double-sampling regression-cum-exponential estimator of the mean of a sensitive variable

Cited by 18 publications

References 22 publications

Median estimation in the presence of non-response using randomised response technique

Median estimation in the presence of non-response using randomised response technique

Development of Estimation Procedure of Population Variance in Stratified Randomized Response Technique

Generalized Difference-Cum Exponential Class of Estimators for Estimating Population Parameters of the Sensitive Variable

Contact Info

Product

Resources

About