Mixture regression cum ratio estimators of population mean under stratified random sampling

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dc.contributor.authorIqbal, Kanwal
dc.date.accessioned2018-01-19T05:04:12Z
dc.date.available2018-01-19T05:04:12Z
dc.date.issued2017
dc.descriptionSupervised by: Dr. Mohammad Moeen Butten_US
dc.description.abstractIn this thesis, single phase Mixture Regression cum ratio Estimators by using auxiliary variables and auxiliary attributes simultaneously have been proposed under Stratified Random Sampling. Special cases of the estimator are discussed and their mean square errors are also derived mathematically. A simulation technique has been used to observe the properties of proposed estimator which shows that the distribution of proposed estimator approximately normal.. An empirical study has been conducted by incorporating quantitative and qualitative characteristics in the form of auxiliary attributes and variables simultaneously to compare the performance of proposed estimator. Comparisons are made with Moeen et al. (2012) single phase mixture regression cum ratio estimator under simple random sampling. It has been found that the mixture regression cum ratio estimator using multiple auxiliary variables and attributes simultaneously under stratified random sampling is more efficient than Moeen et al., (2012) mixture regression cum ratio estimator under simple random samplingen_US
dc.identifier.urihttps://escholar.umt.edu.pk/handle/123456789/2527
dc.language.isoenen_US
dc.publisherUniversity of Management and Technology Lahoreen_US
dc.subjectRatio Estimatorsen_US
dc.subjectMixture Regressionen_US
dc.subjectMS Thesisen_US
dc.titleMixture regression cum ratio estimators of population mean under stratified random samplingen_US
dc.typeThesisen_US
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