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Ratio-Cum-Product Estimator Using Multiple Auxiliary Attributes in Two-Phase Sampling

Open Journal of Statistics 2014年第4期4卷 246-257页

作者： John Kung’u Leo Odongo Department of Mathematics Kenyatta University Nairobi Kenya

In this paper, we have proposed three classes of ratio-cum-product estimators for estimating population mean of study variable for two-phase sampling using multi-auxiliary attributes for full information, partial information and no information cases. The expressions for mean square errors are derived. An empirical study is given to compare the performance of the estimator with the existing estimator that utilizes auxiliary attribute or multiple auxiliary attributes. The ratio-cum-product estimator in two-phase sampling for full information case has been found to be more efficient than existing estimators and also ratio-cum-product estimator in two-phase sampling for both partial and no information case. Finally, ratio-cum-product estimator in two-phase sampling for partial information case has been found to be more efficient than ratio-cum-product estimator in two-phase sampling for no information case.

关键词： Ratio-Cum-Product Estimator Multiple Auxiliary Attributes Two-Phase Sampling and bi-serial Correlation Coefficient

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Ratio-Cum-Product Estimator Using Multiple Auxiliary Attributes in Single Phase Sampling

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Open Journal of Statistics 2014年第4期4卷 239-245页

作者： John Kung’u Leo Odongo Department of Mathematics Kenyatta University Nairobi Kenya

In this paper, we have proposed a class of ratio-cum-product estimator for estimating population mean of study variable for single phase sampling using multi-auxiliary attributes. The expressions for mean square error are derived. An empirical study is given to compare the performance of the estimator with existing estimators. It has been found that the ratio-cum-product estimator using multiple auxiliary attributes is more efficient than mean per unit, product and ratio estimators using one auxiliary attribute, and Product and Ratio estimators using multiple auxiliary attributes in single phase sampling.

关键词： Ratio-Cum-Product Estimator Multiple Auxiliary Attributes Single Phase Sampling bi-serial Correlation Coefficient

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Mixture Regression Estimators Using Multi-Auxiliary Variables and Attributes in Two-Phase Sampling

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Open Journal of Statistics 2014年第5期4卷 355-366页

作者： John John Kung’u Grace Chumba Leo Odongo Department of Mathematics Kenyatta University Nairobi Kenya

In this paper, we have developed estimators of finite population mean using Mixture Regression estimators using multi-auxiliary variables and attributes in two-phase sampling and investigated its finite sample properties in full, partial and no information cases. An empirical study using natural data is given to compare the performance of the proposed estimators with the existing estimators that utilizes either auxiliary variables or attributes or both for finite population mean. The Mixture Regression estimators in full information case using multiple auxiliary variables and attributes are more efficient than mean per unit, Regression estimator using one auxiliary variable or attribute, Regression estimator using multiple auxiliary variable or attributes and Mixture Regression estimators in both partial and no information case in two-phase sampling. A Mixture Regression estimator in partial information case is more efficient than Mixture Regression estimators in no information case.

关键词： Regression Estimator Multiple Auxiliary Variables Multiple Auxiliary Attributes Two-Phase Sampling bi-serial Correlation Coefficient

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Mixture Ratio Estimators Using Multi-Auxiliary Variables and Attributes for Two-Phase Sampling

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Open Journal of Statistics 2014年第9期4卷 776-788页

作者： Paul Mwangi Waweru John Kung’u James Kahiri Department of Statistics and Actuarial Science Kenyatta University Nairobi Kenya

In this paper, we have proposed three classes of mixture ratio estimators for estimating population mean by using information on auxiliary variables and attributes simultaneously in two-phase sampling under full, partial and no information cases and analyzed the properties of the estimators. A simulated study was carried out to compare the performance of the proposed estimators with the existing estimators of finite population mean. It has been found that the mixture ratio estimator in full information case using multiple auxiliary variables and attributes is more efficient than mean per unit, ratio estimator using one auxiliary variable and one attribute, ratio estimator using multiple auxiliary variable and multiple auxiliary attributes and mixture ratio estimators in both partial and no information case in two-phase sampling. A mixture ratio estimator in partial information case is more efficient than mixture ratio estimators in no information case.

关键词： Ratio Estimator Multiple Auxiliary Variables Multiple Auxiliary Attributes Two-Phase Sampling bi-serial Correlation Coefficient

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