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A Modified Regression Estimator for Double Sampling
... of double sampling is necessary if the value of auxiliary variable is obtained by performing a non- destructive experiment whereas to obtain a value of study variable of a unit, a destructive experiment has ... See full document
6
Improved Modified Ratio Estimator for Estimating Population Mean in Double Sampling Using Information on Auxiliary Attribute
... The use of auxiliary information can increase the precision of an estimator when study variable y is highly correlated with auxiliary variable x. There exist situations when information is available in the form of ... See full document
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A Generalized Difference-cum-Ratio Type Estimator for the Population Variance in Double Sampling
... type estimator for the population variance under double sampling ...proposed estimator have been obtained. The comparison of the proposed estimator has been made with the ... See full document
5
A New Regression Type Estimator with Two Auxiliary Variables for Single Phase Sampling
... to double-phase ...single-phase sampling with its properties and identified asymp- totically optimum estimators from the proposed class of ...two-phase sampling. Hanif, Hamad and Shahbaz [15] and ... See full document
9
A new regression type estimator with two auxiliary variables for single-phase sampling
... to double-phase ...single-phase sampling with its properties and identified asymp- totically optimum estimators from the proposed class of ...two-phase sampling. Hanif, Hamad and Shahbaz [15] and ... See full document
9
An Alternative Ratio-Cum-Product Estimator of Finite Population Mean Using Coefficient of Kurtosis of Two Auxiliary Variates in Two-Phase Sampling
... of estimator(s) of population parameter(s). Ratio, product and regression methods are good examples in this ...discussed double sampling procedure using single auxiliary variate whereas [3] ... See full document
10
Effect of Correlation Level on the Use of Auxiliary Variable in Double Sampling for Regression Estimation
... in double sampling procedure increases the precision of an estimate, this pa- per, therefore, suggested for researchers to know that the correlation level between the study variable and the aux- iliary ... See full document
7
Class of Difference Cum Ratio–Type Estimator in Double Sampling Using Two Auxiliary Variables with Some Known Population Parameters
... and regression estimators are the most common and widely discussed in sampling theory ...as regression estimator except when the regression line passes through the ...have ... See full document
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Improvement on estimating median for finite population using auxiliary variables in double-sampling
... the modified versions of median estimators from Singh, ...median estimator in double sampling using information on two auxiliary variables for the finite population ...suggested ... See full document
9
Application of Regression Type Estimator in Double Sampling Skills to Students’ Enrollment in Oyo State
... using Regression Estimation technique with the application of secondary data obtained using the number of students enrollment in 2015 (Auxiliary variable “x”) and 2016 (response variable “y”) respectively in ... See full document
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Some generalized classes of double sampling regression type estimators using auxiliary information
... The proposed generalized classes of esti- mators and are biased and their biases are given by (6) and (13) respectively. The minimum mean square errors of the proposed generalized classes are equal and are given by (9). ... See full document
5
A Comparative Study of Generalized Ratio and Regression Estimators with their classical counterparts
... classical regression estimator performs best when the coefficient of variation for the auxiliary variable Z is least or ...generalized regression estimator performs ... See full document
6
Regression Estimator for Adaptive Cluster Sample
... cluster sampling design is known as a sampling method for rare clustered ...continue sampling in that region. In spatial sampling, adaptive cluster sampling can be provided unbiased ... See full document
5
TWO STAGE LIU REGRESSION ESTIMATOR
... the regression coefficients may be statistically insignificant or have the wrong sign, and they may result in wide confidence intervals for individual ...the regression parameters. One of the most popular ... See full document
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A Modified Statistical Design Model of Double Sampling Control Chart X
... Since Palisade[12] developed Evolver, the GA tool software attached to Microsoft Excel. In this study, Evolver 4.0 is selected for solutions of our modified model. The optimal configurations for number of ... See full document
5
Comparison of estimators for two multi-stage designs when sampling on successive occasions
... 5 the general linear estimator based on the proposed sampling scheme in }.l'has exactly the same precision as the complete estimator based on the new sampling scheme, regardless of the n[r] ... See full document
153
Mixture Regression Cum Ratio Estimator Using Multi Auxiliary Variables and Attributes in Single Phase Sampling
... Conclusion According to Table 1, the proposed mixture regression-cum-ratio estimator using multiple auxiliary variables and attributes using multiple auxiliary variables and attributes h[r] ... See full document
11
IMPROVED EXPONENTIAL ESTIMATOR IN STRATIFIED RANDOM SAMPLING
... 18. Singh, R., Kumar, M., Singh, R.D., and Chaudhary, M.K. (2008): Exponential ratio type estimators in stratified random sampling, Presented in International Symposium on Optimisation and Statistics (I.S.O.S) at ... See full document
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Adjustment of the Auxiliary Variable(s) for Estimation of a Finite Population Mean
... In this section we shall see whether the proposed estimator with transformation y tran f ( ) performs better than the proposed estimator without transformation y prop . In Table 6, we present the numerical ... See full document
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The asymptotic normality of internal estimator for nonparametric regression
... The internal estimator was first proposed by Mack and Müller [4]. Jones et al. [3] stud- ied various kernel-type regression estimators, including the introduced internal estimator (1.2). Linton and ... See full document
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