A class of hybrid type estimators for variance of a finite population in simple random sampling

Sanaullah, Aamir; Niaz, Iqra; Shabbir, Javid; Ehsan, Iqra

doi:10.1080/03610918.2020.1776873

Cited by 7 publications

(3 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ref. [24] proposed hybrid estimators in SRS. Theoretical comparisons and empirical evidence showcase their enhanced efficiency over other estimators.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Variance Estimation in Stratified Random Sampling through a Log-Type Estimator for Finite Populations

Triveni,

Danish,

Albalawi

2024

Symmetry

View full text Add to dashboard Cite

In this research, a logarithmic-type estimator was formulated for estimating the finite population variance in stratified random sampling. By ensuring that the sampling process is symmetrically conducted across the population, biases can be minimized, and the sample is more likely to be representative of the population as a whole. We conducted a comprehensive numerical study and simulation study to evaluate the performance of the proposed estimator. The mean squared error values were computed for both our proposed estimator and several existing ones, including the standard unbiased variance estimator, difference-type estimator, and other considered estimators. The results of the numerical study and simulation study demonstrated that the proposed log-type estimator outperforms the other considered estimators in terms of MSE and percentage relative efficiency. Graphical representations of the results are also provided to illustrate the efficiency of the proposed estimator. Based on the findings of this study, we conclude that the proposed log-type estimator is a valuable addition to the existing literature on variance estimation in stratified random sampling. It provides a more efficient and accurate estimate of the population variance, which can be beneficial for various statistical applications.

show abstract

“…Ref. [24] proposed hybrid estimators in SRS. Theoretical comparisons and empirical evidence showcase their enhanced efficiency over other estimators.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Variance Estimation in Stratified Random Sampling through a Log-Type Estimator for Finite Populations

Triveni,

Danish,

Albalawi

2024

Symmetry

View full text Add to dashboard Cite

show abstract

“…Bhat et al 22 introduced an enhanced estimation procedure for

{S}_y^2

by using the known value of Downton's Method on

X

and Yadav et al 23 suggested new estimation technique for

{S}_y^2

through the modified ratio estimator using known parameters of

X

. Sanaullah et al 24 worked on improved estimation of

{S}_y^2

through a hybrid class of estimators using auxiliary parameters. Muhammad and Amjad 25 introduced a transformed ratio type estimator of

{S}_y^2

utilizing auxiliary parameters.…”

Section: Introductionmentioning

confidence: 99%

“…Singh and Khalid 20 proposed effective estimation strategy and Singh and Khalid 21 proposed composite classes of estimators for variance under the situation of randomized non-response. Bhat et al 22 introduced an enhanced estimation procedure for S 2 y by using the known value of Downton's Method on X and Yadav et al 23 suggested new estimation technique for S 2 y through the modified ratio estimator using known parameters of X. Sanaullah et al 24 worked on improved estimation of S 2 y through a hybrid class of estimators using auxiliary parameters. Muhammad and Amjad 25 introduced a transformed ratio type estimator of S 2 y utilizing auxiliary parameters.…”

mentioning

confidence: 99%

On enhanced estimation and monitoring of population variance using robust auxiliary parameters based estimators

Yadav

Ahmad

Riaz

2022

Concurrency and Computation

View full text Add to dashboard Cite

Summary Searching for efficient estimators of population variance as compared to sample variance has been the key area of interest of the researchers. Auxiliary variable has helped very much in finding estimators more efficient than sample variance. Auxiliary variable is greatly correlated with main study variable. Many authors including Isaki (J Am Stat Assoc 1983, 78, 117) used positively correlated auxiliary variable in the form of various conventional and non‐conventional auxiliary parameters and suggested different ratio type estimators of population variance. In this article, we have suggested a naïve class of variance estimators based on some robust auxiliary parameters, which deals with the outliers in the data. The properties including bias and Mean Square Error (MSE) of suggested family of estimators are studied up to first order of approximation. The theoretical as well as empirical comparison of introduced family of estimators is carried out with competing variance estimators. The estimator with the least MSE is recommended in different areas of applications. At last, the Shewhart type control charts based on the proposed estimators are also studies for application in quality control.

show abstract

Optimal Strategy for Improved Estimation of Population Variance Using Known Auxiliary Parameters

Singh,

Arya,

Yadav

2023

Int. J. Appl. Comput. Math

View full text Add to dashboard Cite

A class of hybrid type estimators for variance of a finite population in simple random sampling

Cited by 7 publications

References 10 publications

Optimizing Variance Estimation in Stratified Random Sampling through a Log-Type Estimator for Finite Populations

Optimizing Variance Estimation in Stratified Random Sampling through a Log-Type Estimator for Finite Populations

On enhanced estimation and monitoring of population variance using robust auxiliary parameters based estimators

Optimal Strategy for Improved Estimation of Population Variance Using Known Auxiliary Parameters

Contact Info

Product

Resources

About