scholarly journals Measuring Performance of Ratio-Exponential-Log Type General Class of Estimators Using Two Auxiliary Variables

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Javid Shabbir ◽  
Shakeel Ahmed ◽  
Aamir Sanaullah ◽  
Ronald Onyango
Keyword(s):  
General Class ◽  
Finite Population ◽  
Real Life ◽  
Auxiliary Variables ◽  
First Order ◽  
Class Of Estimators ◽  
The Mean ◽  
Ratio Estimators ◽  
Efficiency Comparison ◽  
Log Ratio

In this paper, a ratio-exponential-log type general class of estimators is proposed in estimating the finite population mean using two auxiliary variables when population parameters of the auxiliary variables are known. From the proposed estimator, some special estimators are identified as members of the proposed general class of estimators. The mean square error (MSE) expressions are obtained up to the first order of approximation. This study finds that the proposed general class of estimators outperforms as compared to the conventional mean estimator, usual ratio estimators, exponential-ratio estimators, log-ratio type estimators, and many other competitor regression type estimators. Four real-life applications are used for efficiency comparison.

scholarly journals Ameliorated Class of Estimators of Finite Population Variance

2020 ◽  
pp. 1-14
Author(s):  
J. O. Muili ◽  
E. N. Agwamba ◽  
A. B. Odeyale ◽  
A. Adebiyi
Keyword(s):  
Finite Population ◽  
Population Variance ◽  
First Order ◽  
Class Of Estimators ◽  
The Mean ◽  
Ratio Estimators ◽  
Mean Square Errors ◽  
Theoretical Results ◽  
Percentage Relative Efficiency ◽  
Taylor’S Series

A class of ratio estimators of finite population variance is proposed in this study. The properties of the proposed estimators have been derived using Taylor’s Series method up to first order of approximation. The efficiency conditions which are the mean square errors (MSEs) and percentage relative efficiency (PRE) of the proposed estimators over existing estimators have been established. The analytical illustration was also conducted to affirm the theoretical results. The results of the empirical study revealed that the proposed estimators are more efficient than the existing estimators considered in the study.

scholarly journals A Study on the Chain Ratio-Type Estimator of Finite Population Variance

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Yunusa Olufadi ◽  
Cem Kadilar
Keyword(s):  
Finite Population ◽  
Numerical Comparison ◽  
Mean Square ◽  
Auxiliary Variables ◽  
Population Variance ◽  
Two Phase ◽  
First Order ◽  
Phase Sampling ◽  
The Mean ◽  
Two Phase Sampling

We suggest an estimator using two auxiliary variables for the estimation of the unknown population variance. The bias and the mean square error of the proposed estimator are obtained to the first order of approximations. In addition, the problem is extended to two-phase sampling scheme. After theoretical comparisons, as an illustration, a numerical comparison is carried out to examine the performance of the suggested estimator with several estimators.

scholarly journals Estimation of Population Mean in Chain Ratio-Type Estimator under Systematic Sampling

2015 ◽  
Vol 2015 ◽  
pp. 1-5 ◽  
Author(s):  
Mursala Khan ◽  
Rajesh Singh
Keyword(s):  
Finite Population ◽  
Real Data ◽  
Survey Sampling ◽  
Systematic Sampling ◽  
Auxiliary Variables ◽  
Data Set ◽  
Population Mean ◽  
First Order ◽  
The Mean ◽  
A Chain

A chain ratio-type estimator is proposed for the estimation of finite population mean under systematic sampling scheme using two auxiliary variables. The mean square error of the proposed estimator is derived up to the first order of approximation and is compared with other relevant existing estimators. To illustrate the performances of the different estimators in comparison with the usual simple estimator, we have taken a real data set from the literature of survey sampling.

scholarly journals Minimum Covariance Determinant-Based Quantile Robust Regression-Type Estimators for Mean Parameter

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Usman Shahzad ◽  
Nadia H. Al-Noor ◽  
Noureen Afshan ◽  
David Anekeya Alilah ◽  
Muhammad Hanif ◽  
...  
Keyword(s):  
Quantile Regression ◽  
Robust Regression ◽  
Real Life ◽  
Minimum Covariance Determinant ◽  
Mean Squared Errors ◽  
Regression Estimators ◽  
Chi Squared ◽  
Class Of Estimators ◽  
The Mean ◽  
Ratio Estimators

Robust regression tools are commonly used to develop regression-type ratio estimators with traditional measures of location whenever data are contaminated with outliers. Recently, the researchers extended this idea and developed regression-type ratio estimators through robust minimum covariance determinant (MCD) estimation. In this study, the quantile regression with MCD-based measures of location is utilized and a class of quantile regression-type mean estimators is proposed. The mean squared errors (MSEs) of the proposed estimators are also obtained. The proposed estimators are compared with the reviewed class of estimators through a simulation study. We also incorporated two real-life applications. To assess the presence of outliers in these real-life applications, the Dixon chi-squared test is used. It is found that the quantile regression estimators are performing better as compared to some existing estimators.

scholarly journals A Generalized Class of Exponential Type Estimators for Population Mean under Systematic Sampling Using Two Auxiliary Variables

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Mursala Khan
Keyword(s):  
Exponential Type ◽  
Secondary Data ◽  
Estimation Procedure ◽  
The Other ◽  
Systematic Sampling ◽  
Auxiliary Variables ◽  
Population Mean ◽  
First Order ◽  
Class Of Estimators ◽  
The Mean

We have proposed a generalized class of exponential type estimators for population mean under the framework of systematic sampling using the knowledge of two auxiliary variables. The expressions for the mean square error of the proposed class of estimators have been corrected up to first order of approximation. Comparisons of the efficiency of the proposed class of estimators under the optimal conditions with the other existing estimators have been presented through a real secondary data. The statistical study provides strong evidence that the proposed class of estimators in survey estimation procedure results in substantial efficiency improvements over the other existing estimation approaches.

scholarly journals A general class of estimators on estimating population mean using the auxiliary proportions under simple and two phase sampling

2021 ◽  
Vol 6 (12) ◽  
pp. 13592-13607
Author(s):  
Xuechen Liu ◽  
◽  
Muhammad Arslan ◽  
Keyword(s):  
Finite Population ◽  
Two Phase ◽  
Population Mean ◽  
Mean Squared Errors ◽  
First Order ◽  
Mathematical Expressions ◽  
Phase Sampling ◽  
Class Of Estimators ◽  
The Mean ◽  
Two Phase Sampling

<abstract><p>This article deals with estimation of finite population mean using the auxiliary proportion under simple and two phase sampling scheme utilizing two auxiliary variables. Mathematical expressions for the mean squared errors of the proposed estimators are derived under first order of approximation. We compare the proposed class of estimators "theoretically and numerically" with the usual mean estimator of Naik and Gupta <sup>[<xref ref-type="bibr" rid="b1">1</xref>]</sup>. The theoretical as well as numerical findings support the superiority of our proposed class of estimator as compared to estimators available in literature.</p></abstract>

A Class of Estimators of the Population Mean Using Multi­Auxiliary Information

1983 ◽  
Vol 32 (1-2) ◽  
pp. 47-56 ◽  
Author(s):  
S. K. Srivastava ◽  
H. S. Jhajj
Keyword(s):  
Mean Squared Error ◽  
Broad Class ◽  
Auxiliary Variable ◽  
Population Parameters ◽  
Auxiliary Variables ◽  
Sample Mean ◽  
Squared Error ◽  
Class Of Estimators ◽  
The Mean ◽  
Asymptotic Mean Squared Error

For estimating the mean of a finite population, Srivastava and Jhajj (1981) defined a broad class of estimators which we information of the sample mean as well as the sample variance of an auxiliary variable. In this paper we extend this class of estimators to the case when such information on p(> 1) auxiliary variables is available. The estimators of the class involve unknown constants whose optimum values depend on unknown population parameters. When these population parameters are replaced by their consistent estimates, the resulting estimators are shown to have the same asymptotic mean squared error. An expression by which the mean squared error of such estimators is smaller than those which use only the population means of the auxiliary variables, is obtained.

scholarly journals A generalized exponential-type estimator for population mean using auxiliary attributes

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0246947
Author(s):  
Sohail Ahmad ◽  
Muhammad Arslan ◽  
Aamna Khan ◽  
Javid Shabbir
Keyword(s):  
Exponential Type ◽  
Random Sampling ◽  
Finite Population ◽  
Mean Squared Error ◽  
Simple Random Sampling ◽  
Stratified Random Sampling ◽  
Population Mean ◽  
First Order ◽  
Squared Error ◽  
Class Of Estimators

In this paper, we propose a generalized class of exponential type estimators for estimating the finite population mean using two auxiliary attributes under simple random sampling and stratified random sampling. The bias and mean squared error (MSE) of the proposed class of estimators are derived up to first order of approximation. Both empirical study and theoretical comparisons are discussed. Four populations are used to support the theoretical findings. It is observed that the proposed class of estimators perform better as compared to all other considered estimator in simple and stratified random sampling.

scholarly journals Some Median Type Estimators to Estimate the Finite Population Mean

2020 ◽  
pp. 48-58
Author(s):  
Waqar Hafeez ◽  
Javid Shabbir ◽  
Muhammad Taqi Shah ◽  
Shakeel Ahmed
Keyword(s):  
Linear Regression ◽  
Finite Population ◽  
Auxiliary Variable ◽  
Maximum Efficiency ◽  
Order Of Approximation ◽  
Study Variable ◽  
Sample Mean ◽  
First Order ◽  
Regression Estimators ◽  
Class Of Estimators

Researchers always appreciates estimators of finite population quantities, especially mean, with maximum efficiency for reaching to valid statistical inference.  Apart from ratio, product and regression estimators, exponential estimators are widely considered by survey statisticians. Motivated from the idea of exponential type estimators, in this article, we propose some new estimators utilizing known median of the study variable with mean of auxiliary variable. Theoretical properties of the suggested estimators are studied up to first order of approximation. In addition, an empirical and simulation study the comparison of median based proposed class of estimators with sample mean, ratio and linear regression estimators  are discussed. The results expose that the proposed estimators are more efficient than the existing estimators.

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