Information Generating Function of Ranked Set Samples

Omid Kharazmi; Mostafa Tamandi; Narayanaswamy Balakrishnan

doi:10.3390/e23111381

Information Generating Function of Ranked Set Samples

Entropy (Basel). 2021 Oct 21;23(11):1381. doi: 10.3390/e23111381.

Authors

Omid Kharazmi¹, Mostafa Tamandi¹, Narayanaswamy Balakrishnan²

Affiliations

¹ Department of Statistics, Faculty of Mathematical Sciences, Vali-e-Asr University of Rafsanjan, Rafsanjan P.O. Box 518, Iran.
² Department of Mathematics and Statistics, McMaster University, Hamilton, ON L8S 4L8, Canada.

Abstract

In the present paper, we study the information generating (IG) function and relative information generating (RIG) function measures associated with maximum and minimum ranked set sampling (RSS) schemes with unequal sizes. We also examine the IG measures for simple random sampling (SRS) and provide some comparison results between SRS and RSS procedures in terms of dispersive stochastic ordering. Finally, we discuss the RIG divergence measure between SRS and RSS frameworks.

Keywords: Kullback–Leibler divergence; information generating function; ranked set sampling; relative information generating function; simple random sampling.