Statistics

2011 Submissions

[2] viXra:2011.0183 [pdf] replaced on 2021-01-29 20:41:23

Statistical Analysis of the Presidential Elections in Belarus in 2020

Authors: Sergey L. Cherkas
Comments: 7 Pages.

Usually, one wants to have a simple picture of the trustworthiness of the main elections result. However, in some situations only partial information about the elections is available. Here we suggest some criterion of comparing of the available information with the official results. One of the criterions consists in comparison of the mean value over available sample with the official mean value. A Monte Carlo simulation is performed to calculate a probability of the difference between the average value in some random sample and the average over the total set. Another method is an analysis of the nature of the peculiarities in the probability distribution functions consisting in comparison of the probability distribution functions for the percentage and the number of voters for Mr. Lukashenko in each polling station. The last criterion is rather esthetic than exposing. It could be applied to arbitrary elections systems such as United Kingdom or United States if one wants to extract the main result in a few pictures.
Category: Statistics

[1] viXra:2011.0015 [pdf] submitted on 2020-11-02 21:38:17

Probability and Stochastic Analysis in Reproducing Kernels and Division by Zero Calculus

Authors: Tsutomu Matsuura, Hiroshi Okumura, Saburou Saitoh
Comments: 21 Pages.

Professor Rolin Zhang kindly invited in The 6th Int'l Conference on Probability and Stochastic Analysis (ICPSA 2021), January 5-7, 2021 in Sanya, China as a Keynote speaker and so, we will state the basic interrelations with reproducing kernels and division by zero from the viewpoint of the conference topics. The connection with reproducing kernels and Probability and Stochastic Analysis are already fundamental and well-known, and so, we will mainly refer to the basic relations with our new division by zero $1/0=0/0=z/0=\tan(\pi/2) =\log 0 =0, [(z^n)/n]_{n=0} = \log z$, $[e^{(1/z)}]_{z=0} = 1$. 
Category: Statistics