Comparison of unequal probability sampling designs using entropy

Joint Event on 7^th International Conference on Biostatistics and Bioinformatics & 7^th International Conference on Big Data Analytics & Data Mining

September 26-27, 2018 | Chicago, USA

Anam Riaz, Abdul Basit, Zafar Iqbal and Munir Ahmad

National College of Business Administration and Economics, Pakistan

Posters & Accepted Abstracts: J Comput Sci Syst Biol

Abstract :

Entropy measure is the average of information function. In the literature different generalized entropy measures are available for the engineering sciences and reliability theory. In the sampling theory, ranking methodology and Mean Square Error & Variance are widely used for the comparison of different sampling design. In this study entropy and information function are introducing for the comparison of sampling design. In the classical methodology (Rank, MSE, Variance), targeted variable is required for the comparison. By applying entropy and information function, joint probability of inclusion of units is required only rather than the targeted variables. The comparison of both methods has been carried out and found the same results.

Biography :

E-mail: basit_ravian917@hotmail.com