1. Introduction
In the case of effective collection of statistics, one of the priorities is to obtain information according to the principle of ‘‘as
much as possible as quickly as possible’’.Weanalyse the process of capturing packets of any data in this context. It is assumed
that the information measure of these packets is a real random variable having a distribution with a finite dispersion. We
are interested in characterising this type of distribution and estimating its dispersion. The method of capturing data packets
(and also of making inferences about the distribution of information density for all of the packets based on measurement of
these packets) should be optimal, i.e. it should only take into account the necessary part of such packets, i.e. those whose
information measure is one-sidedly bounded by a certain constant a. The above assumptions lead to the development of a
function of information processing intensity which has a surprising property, i.e. it has a maximum at its fixed point. Fixedpoint
equation is used to estimate the dispersion of a distribution.
Fixed-point theorems constitute a fascinating object of study. Since its beginnings, the development of fixed-point
theory has been connected with its numerous applications in other fields of mathematics as well as in game theory and
economics [1,2]. Naturally, fixed-point theorems are also used to learn about the distribution of a characteristic within
a population based on data obtained from a sample, which is an incredibly important problem in the natural and social