MODIFICATION OF SEPARATE RATIO TYPE EXPONENTIAL ESTIMATOR: A POST-STRATIFICATION APPROACH

2021 ◽  
Vol 5 (2) ◽  
pp. 404-412
Author(s):  
Adam Rabiu ◽  
Abubakar Yahaya ◽  
Muhammad Abdulkarim
Keyword(s):  
Mean Square Error ◽  
Relative Efficiency ◽  
Empirical Studies ◽  
Degree Of Approximation ◽  
Mean Square ◽  
Percentage Relative Efficiency ◽  
Post Stratification

In this research, modification of separate ratio type exponential estimator introduced in an earlier study is proposed. Expressions for the bias and mean square error (MSE) of the proposed estimator up to first degree of approximation are derived. The optimum value of the constant which minimize the MSE of the suggested estimator is also obtained. In the same vein, efficiency comparisons between the proposed estimator and some related existing ones under the case of post-stratification is conducted. Empirical studies have been conducted to demonstrate the efficiencies of the suggested estimators over other considered estimators. The proposed MSE and Percentage Relative Efficiency (PRE) were used to evaluate the achievement of the modified estimator.

scholarly journals A Class of Estimator for Population Mean Under SRS

2020 ◽  
Vol 2 (1) ◽  
pp. 9-26
Author(s):  
Syed Abdul Rehman ◽  
Mohammad Asif
Keyword(s):  
Mean Square Error ◽  
Auxiliary Information ◽  
Degree Of Approximation ◽  
Mean Square ◽  
Population Mean ◽  
Class Of Estimators ◽  
Efficiency Comparison

In this paper we propose a class of estimators for the estimation of finitepopulation mean using the auxiliary information when SRS scheme is used. Theexpressions for the Bias and mean square error (MSE) of the existing andsuggested class of estimators are derived up to first degree of approximation andthe efficiency comparison of suggested class of estimators is made with otherexisting estimators, using both theoretically and numerically based on realpopulation sets.

Estimating volumes from systematic hyperplane sections

1985 ◽  
Vol 22 (3) ◽  
pp. 518-530 ◽  
Author(s):  
Luis-M. Cruz-Orive
Keyword(s):  
Mean Square Error ◽  
Empirical Studies ◽  
Volume Ratio ◽  
Theoretical Models ◽  
Volume Estimation ◽  
Ratio Estimator ◽  
Mean Square ◽  
Drastic Increase ◽  
The Mean ◽  
Hyperplane Sections

A theory for volume estimation from independent, unbounded plane probes is available. In practice, however, probes cannot be unbounded and independent at the same time, hence the interest of systematic sectioning. Previous empirical studies on real specimens showed that the mean square error of a volume ratio estimator obtained from m systematic sections behaved roughly as m–3 for small m. This drastic increase in efficiency with respect to independent sectioning prompted us to develop some theoretical models in this paper. We study specimens consisting of two ellipsoids in Rn. In virtue of an invariance result, an ellipsoid–ellipsoid model can be studied via a simple model consisting of two concentric n-balls. Explicit results are obtained for n = 1 and n = 3. In the latter case the bias and the mean square error of the relevant volume ratio estimator are both shown to be of O (m–4).

scholarly journals Families of estimators for ratio and product of study characters using mean and proportion of auxiliary character in presence of non-response

2016 ◽  
Vol 4 (2) ◽  
pp. 142
Author(s):  
Raghaw Sinha
Keyword(s):  
Mean Square Error ◽  
Minimum Mean Square Error ◽  
Real Data ◽  
Degree Of Approximation ◽  
Data Sets ◽  
Mean Square ◽  
Population Means ◽  
Auxiliary Character

In this paper, families of estimators for ratio and product of two population means are suggested using proportion and mean of auxiliary character in presence of non-response. The bias and mean square error (MSE) of the proposed families of estimators are obtained up to the first degree of approximation under two different cases. The specified conditions under which the members of proposed families of estimators attain minimum mean square error have been obtained. Theoretical and empirical comparisons based on real data sets are made to show that the suggested families of estimators are more efficient than the relevant estimators such as usual conventional estimator, (Khare & Sinha 2012 a) estimators and (Sinha 2014) estimators.

scholarly journals A Class of Estimators for Finite Population Mean in Double Sampling under Nonresponse Using Fractional Raw Moments

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Manzoor Khan ◽  
Javid Shabbir ◽  
Zawar Hussain ◽  
Bander Al-Zahrani
Keyword(s):  
Empirical Study ◽  
Mean Square Error ◽  
Finite Population ◽  
Degree Of Approximation ◽  
Double Sampling ◽  
Mean Square ◽  
Population Mean ◽  
Class Of Estimators ◽  
Better Than

This paper presents new classes of estimators in estimating the finite population mean under double sampling in the presence of nonresponse when using information on fractional raw moments. The expressions for mean square error of the proposed classes of estimators are derived up to the first degree of approximation. It is shown that a proposed class of estimators performs better than the usual mean estimator, ratio type estimators, and Singh and Kumar (2009) estimator. An empirical study is carried out to demonstrate the performance of a proposed class of estimators.

Estimating volumes from systematic hyperplane sections

1985 ◽  
Vol 22 (03) ◽  
pp. 518-530 ◽  
Author(s):  
Luis-M. Cruz-Orive
Keyword(s):  
Mean Square Error ◽  
Empirical Studies ◽  
Volume Ratio ◽  
Theoretical Models ◽  
Volume Estimation ◽  
Ratio Estimator ◽  
Mean Square ◽  
Drastic Increase ◽  
The Mean ◽  
Hyperplane Sections

A theory for volume estimation from independent, unbounded plane probes is available. In practice, however, probes cannot be unbounded and independent at the same time, hence the interest of systematic sectioning. Previous empirical studies on real specimens showed that the mean square error of a volume ratio estimator obtained from m systematic sections behaved roughly as m–3 for small m. This drastic increase in efficiency with respect to independent sectioning prompted us to develop some theoretical models in this paper. We study specimens consisting of two ellipsoids in Rn. In virtue of an invariance result, an ellipsoid–ellipsoid model can be studied via a simple model consisting of two concentric n-balls. Explicit results are obtained for n = 1 and n = 3. In the latter case the bias and the mean square error of the relevant volume ratio estimator are both shown to be of O (m –4).

scholarly journals REGRESSION-IN-RATIO ESTIMATORS IN THE PRESENCE OF OUTLIERS BASED ON REDESCENDINGM-ESTIMATOR

2019 ◽  
pp. 01-10
Author(s):  
Aamir Raza ◽  
Muhmmad Noor-ul-Amin ◽  
Muhammad Hanif
Keyword(s):  
Mean Square Error ◽  
Taylor Series ◽  
Simulation Study ◽  
Relative Efficiency ◽  
Mean Square ◽  
Extensive Simulation ◽  
Taylor Series Approximation ◽  
Series Approximation ◽  
M Estimator ◽  
Ratio Estimators

In this paper, a robust redescending M-estimator is used to construct the regression-inratio estimators to estimate population when data contain outliers. The expression of mean square error of proposed estimators is derived using Taylor series approximation up to order one. Extensive simulation study is conducted for the comparison between the proposed and existing class of ratio estimators. It is revealed form the results that proposed regression-in-ratio estimators have high relative efficiency (R.E) as compared to previously developed estimators. Practical examples are also cited to validate the performance of proposed estimators.  

The Bordeaux Automatic Meridian Circle

1978 ◽  
Vol 48 ◽  
pp. 227-228
Author(s):  
Y. Requième
Keyword(s):  
Mean Square Error ◽  
Mean Square ◽  
Meridian Circle ◽  
The Mean ◽  
Full Automation

In spite of important delays in the initial planning, the full automation of the Bordeaux meridian circle is progressing well and will be ready for regular observations by the middle of the next year. It is expected that the mean square error for one observation will be about ±0.”10 in the two coordinates for declinations up to 87°.

Investigation of Accuracy of a Calibrated Estimator of a Ratio by Modelling

2005 ◽  
Vol 10 (4) ◽  
pp. 333-342
Author(s):  
V. Chadyšas ◽  
D. Krapavickaitė
Keyword(s):  
Mean Square Error ◽  
Taylor Series ◽  
Random Sampling ◽  
Finite Population ◽  
Taylor Series Expansion ◽  
Simple Random Sampling ◽  
Population Parameter ◽  
Mean Square ◽  
Parameter Ratio ◽  
Using Data

Estimator of finite population parameter – ratio of totals of two variables – is investigated by modelling in the case of simple random sampling. Traditional estimator of the ratio is compared with the calibrated estimator of the ratio introduced by Plikusas [1]. The Taylor series expansion of the estimators are used for the expressions of approximate biases and approximate variances [2]. Some estimator of bias is introduced in this paper. Using data of artificial population the accuracy of two estimators of the ratio is compared by modelling. Dependence of the estimates of mean square error of the estimators of the ratio on the correlation coefficient of variables which are used in the numerator and denominator, is also shown in the modelling.

Performance analysis of global local mean square error criterion of stochastic linearization for nonlinear oscillator

2019 ◽  
Author(s):  
Nguyen Cao Thang ◽  
Luu Xuan Hung
Keyword(s):  
Performance Analysis ◽  
Mean Square Error ◽  
Nonlinear Oscillators ◽  
Degree Of Freedom ◽  
Equivalent Linearization ◽  
Mean Square ◽  
Error Criterion ◽  
Stochastic Linearization ◽  
Local Mean ◽  
Mean Square Error Criterion

The paper presents a performance analysis of global-local mean square error criterion of stochastic linearization for some nonlinear oscillators. This criterion of stochastic linearization for nonlinear oscillators bases on dual conception to the local mean square error criterion (LOMSEC). The algorithm is generally built to multi degree of freedom (MDOF) nonlinear oscillators. Then, the performance analysis is carried out for two applications which comprise a rolling ship oscillation and two degree of freedom one. The improvement on accuracy of the proposed criterion has been shown in comparison with the conventional Gaussian equivalent linearization (GEL).

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