Conditions of obtaining the discrete kurtosis spectrum of statistical distributions of biometric data for small samples
Journal of computational and engineering mathematics, Tome 4 (2017) no. 4, pp. 53-63.

Voir la notice de l'article provenant de la source Math-Net.Ru

The aim of the paper is to amplify the statistic criterions in small test samples. We propose to use the simulation tools and numerically get the density of distribution of statistical excess criterion values in small samples. The spectrum of excess criterion states becomes discrete, when the histogram intervals are synchronized with the mathematical expectation of the sample. The chi-square Pearson's molecule constructed before was created with the use of the second-order statistical moment. In this paper, we prove that such constructions are also efficient for forth-order statistical moments. The chi-square mathematical Pearson's molecule and mathematical excess molecule are analogous. We surmise that there are infinitely many mathematical molecules, which are similar to the actual physical molecules in their properties. The Schrödinger equations are not unique; their analogues can be constructed for each mathematical molecule. We can expect a synthesis of the mathematical molecules with inner multidimensional continuum states of "electrons" and their displays in the form of discrete output spectrums of states for sixth-, eighth-order and higher even statistical moments.
Keywords: quantum superposition, chi-square Pearson's criterion, discrete spectrum of states, statistical analysis of small samples.
@article{JCEM_2017_4_4_a4,
     author = {V. I. Volchikhin and A. I. Ivanov and A. I. Gazin and A. G. Bannykh},
     title = {Conditions of obtaining the discrete kurtosis spectrum of statistical distributions of biometric data for small samples},
     journal = {Journal of computational and engineering mathematics},
     pages = {53--63},
     publisher = {mathdoc},
     volume = {4},
     number = {4},
     year = {2017},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/JCEM_2017_4_4_a4/}
}
TY  - JOUR
AU  - V. I. Volchikhin
AU  - A. I. Ivanov
AU  - A. I. Gazin
AU  - A. G. Bannykh
TI  - Conditions of obtaining the discrete kurtosis spectrum of statistical distributions of biometric data for small samples
JO  - Journal of computational and engineering mathematics
PY  - 2017
SP  - 53
EP  - 63
VL  - 4
IS  - 4
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/JCEM_2017_4_4_a4/
LA  - en
ID  - JCEM_2017_4_4_a4
ER  - 
%0 Journal Article
%A V. I. Volchikhin
%A A. I. Ivanov
%A A. I. Gazin
%A A. G. Bannykh
%T Conditions of obtaining the discrete kurtosis spectrum of statistical distributions of biometric data for small samples
%J Journal of computational and engineering mathematics
%D 2017
%P 53-63
%V 4
%N 4
%I mathdoc
%U http://geodesic.mathdoc.fr/item/JCEM_2017_4_4_a4/
%G en
%F JCEM_2017_4_4_a4
V. I. Volchikhin; A. I. Ivanov; A. I. Gazin; A. G. Bannykh. Conditions of obtaining the discrete kurtosis spectrum of statistical distributions of biometric data for small samples. Journal of computational and engineering mathematics, Tome 4 (2017) no. 4, pp. 53-63. http://geodesic.mathdoc.fr/item/JCEM_2017_4_4_a4/

[1] G. A. Korn, T. M. Korn, Mathematical Handbook for Scientists and Engineers, McGraw-Hill Book Company, New York, San Francisco, Toronto, London, Sydney, 1968 | DOI | MR | MR

[2] B. B. Akhmetov, A. I. Ivanov, N. I. Serikova, Yu. V. Funtikova, “Diskretnyi kharakter zakona raspredeleniya khi-kvadrat kriteriya dlya malykh testovykh vyborok”, Vestnik Natsionalnoi akademii nauk Respubliki Kazakhstan, 2015, no. 1, 17–25

[3] B. Akhmetov, A. Ivanov, A. Gilmutdinov, A. Bezyaev, Y. Funtikova, “The Family of Chi-Square Molecules Pearson: Software-Continuum Quantum accelerators of Hhigh- Dimensional Calculations”, 15th International Conference on Control, Automation and Systems (ICCAS 2015), Proceedings of the International Conference (Korea, Busan, 2015, October 13-16), Busan, 2015, 1337–1341 | DOI

[4] V. Kulagin, A. Ivanov, A. Gazin, B. Akhmetov, “Tsiklicheskie kontinualno-kvantovye vychisleniya: usilenie moschnosti khi-kvadrat kriteriya na malykh vyborkakh”, Analitika, 2016, no. 5, 22–29

[5] V. I. Volchikhin, A. I. Ivanov, D. V. Paschenko, B. B. Akhmetov, S. E. Vyatchanin, “Perspektiva sozdaniya tsiklicheskoi kontinualno-kvantovoi khi-kvadrat mashiny dlya proverki statisticheskikh gipotez na malykh testovykh vyborkakh biometricheskikh dannykh i dannykh inoi prirody”, Izvestiya vysshikh uchebnykh zavedenii. Povolzhskii region. Tekhnicheskie nauki, 2017, no. 1 (41), 5–15

[6] V. I. Volchikhin, A. I. Ivanov, A. V. Serikov, Yu. I. Serikova, “Ispolzovanie effektov kvantovoi superpozitsii pri regulyarizatsii vychislenii standartnogo otkloneniya na malykh vyborkakh biometricheskikh dannykh”, Izmerenie. Monitoring. Upravlenie. Kontrol, 2017, no. 1, 57–63

[7] A. I. Ivanov, Mnogomernaya neirosetevaya obrabotka biometricheskikh dannykh s programmnym vosproizvedeniem effektov kvantovoi superpozitsii, Izd-vo \flqq PNIEI\frqq , Penza, 2016

[8] M. Nielsen, I. Chuang, Quantum Computation and Quantum Information, Cambridge University Press, New York, 2006 | MR

[9] V. I. Volchikhin, B. B. Akhmetov, A. I. Ivanov, “Bystryi algoritm simmetrizatsii korrelyatsionnykh svyazei biometricheskikh dannykh vysokoi razmernosti”, Izvestiya vysshikh uchebnykh zavedenii. Povolzhskii region. Tekhnicheskie nauki, 2016, no. 1 (37), 5–15