In industrial, environmental, and ecological investigations, ranked set sampling is a sample method that enables the experimenter to use the whole range of population values. The ranked set sampling process can be modified in two extremely helpful ways: maximum ranked set sampling with unequal samples and minimum ranked set sampling with unequal samples. They permit an increase in set size without too many ranking errors being introduced. In this paper, we are defining general weighted extropy (GWJ) of minimum and maximum ranked set samples when samples are of unequal size (minRSSU and maxRSSU, respectively). Stochastic comparison and monotone properties have been studied under different situations. Additionally, we compare the extropy of these two sampling data with that of ranked set sampling data and simple random sampling data. Finally, Bounds of GWJ of minRSSU and maxRSSU have been obtained.

翻译：在工业、环境和生态调查中，排序集抽样是一种能使实验者利用总体值全范围的抽样方法。排序集抽样过程可通过两种极为有用的方式进行改进：不等样本最大排序集抽样和不等样本最小排序集抽样。这两种方法允许在不引入过多排序误差的前提下增加集的大小。本文定义了当样本大小不等时（分别为minRSSU和maxRSSU），最小和最大排序集样本的广义加权外熵（GWJ）。研究了不同情况下的随机比较和单调性性质。此外，我们将这两种抽样数据的外熵与排序集抽样数据和简单随机抽样数据的外熵进行了比较。最后，得到了minRSSU和maxRSSU的GWJ界限。