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dc.contributor.authorMulwa, Damaris Felistus
dc.contributor.authorOrwa, George Otieno
dc.contributor.authorOtieno, Romanus Odhiambo
dc.date.accessioned2018-11-24T09:02:44Z
dc.date.accessioned2020-02-06T14:01:23Z
dc.date.available2018-11-24T09:02:44Z
dc.date.available2020-02-06T14:01:23Z
dc.date.issued2018
dc.identifier.citationMulwa, D. F., Orwa, G. O., & Odhiambo, R. Robust Estimation of Finite Population Totals Using a Model Based Approach in the Presence of Two Auxiliary Variables.en_US
dc.identifier.urihttp://repository.must.ac.ke/handle/123456789/974
dc.description.abstractThe utilization of auxiliary information during surveys increases the accuracy of estimators, thereby giving more reliable estimates of the population parameters of interest. It has been established that the presence of more than one auxiliary variables, some more robust estimators can be formed by combining different estimators like product, ratio or even regression estimators and in each case the individual estimators uses its own random variable. One of the most commonly used methods is the ratio method of estimating finite totals which is the foundation of all the other methods that use auxiliary information. In this paper, an estimator of the ratio-exponential class that uses two auxiliary variables has been proposed and its variance derived. After deriving the proposed estimator the coverage probabilities were estimated. Results showed that the interval length of the proposed estimator was narrower and tighter than that of the known Horwitz-Thompson’s estimator. Two datasets from the agricultural and environmental sectors were used in order to investigate the properties of the estimator and they gave satisfactory results. Mean squared error criteria was used to investigate the performance of the proposed estimator and in both cases it had the minimum squared error values. The analysis in these paper is of very great importance in understanding environmental and agricultural data.en_US
dc.language.isoenen_US
dc.publisherInternational Journal of Data Science and Analysisen_US
dc.subjectAuxiliary Variable, Coverage Probabilities, Precision, Predictive Approachen_US
dc.titleRobust Estimation of Finite Population Totals Using a Model Based Approach in the Presence of Two Auxiliary Variablesen_US
dc.typeArticleen_US


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