Parameter estimation by fixed point of function of information processing intensity

Abstract

We present a new method of estimating the dispersion of a distribution which is based on the surprising property of a function that measures information processing intensity. It turns out that this function has a maximum at its fixed point. We use a fixed-point equation to estimate the parameter of the distribution that is of interest to us. We illustrate the estimation method by using the example of an exponential distribution. The codes of programs that calculate the experimental values of the information processing intensity are presented.

The intensity of the random variable intercept in the sector of negative probabilities

“…The properties of (1) were studied previously in classic and quantum market games [1,2,3] and in information theory context [4,5,6]. We envisage that the proposed approach has potential interesting applications in statistics (parameter estimation) [7].…”

“…Brouwer theorem, Banach contraction mapping principle, etc.). Such problems were from the beginning closely related to their applications in fields such as game theory and economics [11], statistics [7] and many other [12,13]. In this paper we have examined the measurement intensity of a random variable in the sector of negative probabilities.…”