Bio
Dr. Sanjib Choudhury is a dedicated academic and researcher affiliated with the Department of Mathematics at the North Eastern Regional Institute of Science and Technology (NERIST) in Nirjuli, Arunachal Pradesh, India. His research primarily focuses on sampling techniques and survey methodology, with a particular emphasis on developing efficient estimators for finite population means. Dr. Choudhury has authored several notable works, including 'An Efficient Class of Dual to Product-Cum- Dual to Ratio Estimators of Finite Population Mean in Sample Surveys,' 'Exponential Chain Ratio and Product type Estimators for Finite Population Mean under Double Sampling Scheme,' and 'An Efficient Class of Ratio-Cum-Dual to Product Estimator of Finite Population Mean in Sample Surveys.' With a strong background in mathematics and statistics, he has contributed significantly to the field of operations research and management science methods. Dr. Choudhury holds a Ph.D. in Sampling Techniques and has been actively involved in peer review for academic journals. His work has garnered attention, with over 100 citations and an h-index of 7, reflecting his impact on the scientific community.
Educational Journey
North Eastern Regional Institute of Science and Technology
B. Sc, M. Sc., M. Phil, Ph.D • Sampling Techniques
M.Sc., M. Phil
Experience
North Eastern Regional Institute of Science and Technology
0 - 0 • MathematicsResearch
An Efficient Class of Ratio-Cum-Dual to Product Estimator of Finite Population Mean in Sample Surveys
We consider a class of ratio-cum-dual to product estimator for estimating a finite population mean of the study variate. The bias and mean square error of the proposed estimator have been obtained. The asymptotically optimum estimator (AOE) in this class has also been identified along with its approximate bias and mean square error. Theoretical and empirical studies have been done to demonstrate the superiority of the proposed estimator over the other estimators.
Exponential Chain Ratio and Product type Estimators for Finite Population Mean under Double Sampling Scheme
In this paper an exponential chain ratio and product type estimators in double sampling have been developed for estimating finite population mean of the study variable when the information on another additional auxiliary character is available along with the main auxiliary character. The bias and mean square error of the proposed estimators have been obtained in two different cases. Theoretical and empirical studies have been done to demonstrate the efficiency of the proposed strategy with respect to the strategies which utilizes the information on one and two auxiliary characteristics.
An Efficient Class of Dual to Product-Cum- Dual to Ratio Estimators of Finite Population Mean in Sample Surveys
This paper considers a class of dual to product-cum-dual to ratio estimators for estimating finite population mean of the study variate using auxiliary variate. The bias and mean square error of the proposed estimator have been obtained. The asymptotically optimum estimator (AOE) in the class has also been identified along with its approximate bias and mean square error. Theoretical and empirical studies have been done to demonstrate the superiority of the proposed estimators over the other estimators.
