M. Tahir, Bu Yude, S. Bashir, S. Hussain, T. Munir
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引用次数: 0
Abstract
In this manuscript, the mean of the study and the auxiliary variable, as well as the rank of the auxiliary variable, were needed to develop a new, improved ratio-in-regression type estimator for population mean. Up to the first order of approximation, expressions for the bias and mean square error of the existing and proposed estimators are computed. The effectiveness and stability of our new, enhanced estimator are evaluated using simulation and two actual data sets. The suggested estimator's superior performance to all other considered estimators is shown both conceptually and numerically. The mean square error is the lowest, and PREs out-performs other known estimators by a factor of more than one hundred. Overall, we draw the conclusion that the suggested new improved estimator outperforms all its predecessors.
期刊介绍：
Management Science Letters is a peer reviewed, monthly publication dedicated to create a forum for scientists in all over the world who wish to share their experiences and knowledge in the field of management skills in the form of original, high quality and value added articles. The journal''s policy is to perform a peer review on all submitted articles and the papers will be appeared in a form of online on our website as soon as the review result becomes positive. The journal covers both empirical and theoretical aspects of management and gives the chance on sharing knowledge among practitioners. Management Science Letters is dedicated for publishing in the following areas: • Quality Management • Production Management (Scheduling, Production management, etc.) • Total Quality Management (TQM) • Six Sigma • Production Efficiency • Just in Time Inventory • Data Envelopment Analysis • Balanced Score Card • Activity Based Cost (ABC) • Technology Acceptance Model • Marketing planning and Customer Relationship Management • Critical Success Factors • e-learning • Customer satisfaction, Job satisfaction, Job turnover, • Organizational commitment, Employee Commitment • Knowledge Management • Knowledge sharing • Human Resources Management (Employee training, Employee Performance, Work achievements,) • Small and medium-sized enterprises (SMEs) issues and Economic development • Innovation, Creativity, Productivity and Performance • Multi-Criteria Decision Making Applications in Management Science (AHP, BWM, TOPSIS, …) • Education Management, Social development, Public Policy • Tourism Industry, Tourism promotion, Tourism directorates • Business performance and financial performance
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