A weighted entropy measure of information is provided by a probabilistic experiment whose basic events are described by their objective probabilities and some qualitative (objective or subjective) weights. These measures have tremendous applications and are found to be quite helpful in many fields. In this paper, a new weighted entropy measure is developed for the discrete distributions when probabilities are unknown and weights are known. The various characteristics of the measure are investigated. The proposed weighted information measure is found useful when standard distributions are not appropriate and we require to study weighted distribution. In situations, weights of the distribution are considered as its probabilities the new measure reduces to well known Shannon (1948) entropy. The measure is also studied taking into account a particular case.
Volume 11 | 01-Special Issue
Pages: 1264-1271