Error of the capacity method of rare events analysis, remoteness from the end user
News of the Kabardin-Balkar scientific center of RAS, no. 3 (2019), pp. 48-77.

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The works devoted to the study of rare events are very few. The most popular method for analyzing rare events is the theory of random processes, when events are represented by Poisson or Palm flows. Other methods have even less accuracy and validity. Nevertheless, the theory of random processes is not able to determine the event occurrence moment but only the probability of a given number of events for a fixed length time interval. The paper describes the methodology for the rare events study, which is based on the difference in the events sources and the restoration of the proposed process parameters underlying the occurrence of these events. After the restoration of the process parameters, a pattern is sought by any other known methods, after which the patterns are extrapolated for the future. After extrapolating the process parameters, the process starts to obtain a forecast of the time moments of the following events occurrence. The most common process in the economy is the process of consuming, or expenditure of products, or accumulating disturbances to a certain level. In this case, event sources can be modeled as capacities. The process parameter is the emptying speed of this capacity. A method for restoring this speed is proposed, after which future events can be predicted. I call this method of analyzing and predicting rare events the “capacity” method. The article analyzes the influence of the position in the chain of distributors on the accuracy of restoring the original unknown function of the products consumption rate using the capacity method. Another goal is to find the magnitude of the relative error in the restoration of the original unknown function of product consumption. With the help of mathematical analysis, the consumption process for the chain of distributors is considered, the inverse problem is constructed, the error is analyzed. As a result of the current study, the values of the error in restoring the original dependence in the sale of products through one intermediary, as well as in the sale of products through two successive intermediaries, are obtained. The extreme values of the intervals for the error of restoring the original dependence were obtained. On a specific numerical example, the validity of the formulas obtained is confirmed. It is shown that the error is not systematic. It is shown that the increase in error from the distance from the end user, with all other factors remaining unchanged, grows as a sum of a geometrically decreasing progression. Values of the variance and standard deviation for the relative error were calculated; it is shown that they grow very slowly.
Keywords: rare events; capacity method; consumption rate; accuracy; error; dispersion; sequence of distributors; intermediaries.
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Yu. A. Korablev. Error of the capacity method of rare events analysis, remoteness from the end user. News of the Kabardin-Balkar scientific center of RAS, no. 3 (2019), pp. 48-77. http://geodesic.mathdoc.fr/item/IZKAB_2019_3_a3/

[1] J. Dudewicz Edward, A. Karian Zaven, “The role of statistics in is/it: practical gains from mined data”, Information systems frontiers, 1999, no. 1 (3), 259–266 | DOI

[2] S. Makridakis, “Forecasting: its role and value for planning and strategy”, International journal of forecasting, 1996, no. 12 (4), 513–537 | DOI

[3] S. Saerkkae, Bayesian Filtering and Smoothing, Cambridge University Press, 2013 (data obrascheniya: 03.03.2019) http://www.cambridge.org/9781107030657 | Zbl

[4] Lambert Koopmans, The Spectral Analysis of Time Series. 1st Edition., University of New Mexico. Academic Press, 1995 (data obrascheniya: 03.03.2019) https://www.elsevier.com/books/the-spectral-analysis-of-time-series/koopmans/978-0-12-419251-5 | MR

[5] Yu. P. Lukashin, Adaptivnyye metody kratkosrochnogo prognozirovaniya vremennykh ryadov [Adaptive methods of short-term forecasting of time series], Finance and statistics, M, 2003

[6] A. N. Golubinsky, “Metody approksimatsii eksperimental'nykh dannykh i postroyeniya modeley [Methods of approximation of experimental data and model building]”, Vestnik Voronezhskogo instituta MVD Rossii [Bulletin of the Voronezh Institute of the Ministry of Internal Affairs of Russia], 2007, no. 2, 138–143

[7] J. E. Jackson, “Principal components and factor analysis: principal components”, Journal of Quality Technology, 1980, no. 12, 201–213

[8] J. E. Jackson, “Principal components and factor analysis: additional topics related to principal components”, Journal of Quality Technology, 1981, no. 13, 46–58

[9] Korrektirovka chisla redkikh sobytiy v logisticheskoy regressii [Adjustment of the number of rare events in the logistic regression http://www.statmethods.ru/stati/178-korrektirovka-chisla-redkikh-sobytij-v-modeli-logisticheskoj-regressii.html

[10] N. S. Altman, “An introduction to kernel and nearest-neighbor nonparametric regression”, The American Statistician, 1992, no. 46 (3), 175–185 | DOI | MR

[11] J. D. Croston, “Forecasting and stock control for intermittent demands”, Operational Research Quarterly (1970-1977), 1972, no. 23 (3), 289–303 | Zbl

[12] F. R. Johnston, J. E. Boylan, “Forecasting intermittent demand: a comparative evaluation of Croston's method. Comment”, International journal of forecasting, 1996, no. 12 (2), 297–298

[13] B. Efron, R. J. Tibshirani, “An introduction of the Bootstrap”, New York: Chapman Hall, 1993 | MR

[14] T. R. Willemain, D. S. Park, Y. B. Kim, K. I. Shin, “Simulation output analysis using the threshold bootstrap”, Eur J Oper Res, 2001, no. 134 (1), 17–28 | MR | Zbl

[15] R. S. Ivanko, Kratkosrochnoye prognozirovaniye nestatsionarnogo sprosa v optovoy torgovle, dis. kand. ekonom. nauk [Short-term forecasting of non-stationary demand for whole-sale trade: thesis for Cand. of economics], Moscow, 2005

[16] E. S. Wentzel, L. A. Ovcharov, Teoriya sluchaynykh protsessov i yeye inzhenernyye prilozheniya [The theory of random processes and its engineering applications], Ucheb. posobiye dlya vtuzov [Training manual for technical colleges], 2nd ed., Sr, Higher. school, 2000, 383 pp.

[17] M. M. Zhukov, V. I. Kudryash, “Matematicheskaya model' riskov raspredelennykh tekhnicheskikh sistem pri beta-raspredelenii plotnosti veroyatnosti nastupleniya ushcherba [Mathematical model of risks of distributed technical systems for beta-distribution of density of probability of suffering of damage]”, Obshchestvennaya bezopasnost', zakonnost' i pravoporyadok v III tysyacheletii, 2017, no. 3-3, 278–281, Voronezhskii institut MVD RF, Voronezh

[18] I. T. Dzanagova, L. T. Khugaeva, “Informatsionno-statisticheskiye metody postroyeniya ekstremal'nykh modeley redkikh sobytiy [Method of operator series for constructing extremal models of rare events]”, Fundamental'nye issledovaniya, 2015, no. 11-6, 1081–1084, Akademiya Estestvoznaniya, Penza

[19] V. Lukinsky, D. Zamaletdinova, “Metody upravleniya zapasami: raschet pokazateley zapasa dlya tovarnykh grupp, otnosyashchikhsya k redkim sobytiyam (chast' I) [Methods of inventory management: the calculation of inventory indicators for product groups related to rare events (Part I)]”, Logistika, 2015, no. 1 (98), 28–33

[20] V. Lukinsky, D. Zamaletdinova, “Metody upravleniya zapasami: raschet pokazateley zapasa dlya tovarnykh grupp, otnosyashchikhsya k redkim sobytiyam (chast' II) [Methods of inventory management: the calculation of inventory indicators for product groups related to rare events (Part II)]”, Logistika, 2015, no. 2 (99), 24–27

[21] A. P. Vozhzhov, O. V. Lunyakov, S. P. Vozhzhov, “Formirovaniye strakhovykh zapasov predpriyatiya pri puassonovskom kharaktere postupayushchikh i vydavayemykh potokov [For-mation of safety stock with application of the Poisson processes to incoming and outgoing flows]”, Ekonomika i upravlenie: teorija i praktika [Economics and Management: Theory and Practice], 2015, no. 1 (1), 30–35

[22] Yu. A. Korablev, “Yemkostnyy metod opredeleniya funktsii skorosti potrebleniya [Capacity method of determination consumption rate function]”, Ekonomika i menedzhment sistem uprav-leniya [Economics and management systems management], 1:15(1.1) (2015), 140–150, Izd-vo «Nauchnaya kniga», Voronezh

[23] Yu. A. Korablev, “Obosnovaniye yemkostnogo metoda opredeleniya sprosa [Argumentation of capacity method demand determination]”, Ekonomika, statistika i informatika. Vestnik UMO [Economy, statistics and computer science. Herald UMO], 2015, no. 5, 96–101, REU Im. Plehanova, M

[24] Yu. A. Korablev, “Issledovaniye tochnosti yemkostnogo metoda ot pozitsii v tsepochke rasprostraniteley [The study of the capacitive method accuracy from the position in the chain of distributors]”, Ekonomika i upravlenie: problemy, resheniya [Economics and Management: problems, solutions], 2018, no. 7 (5), 106–121, Nauchnaya biblioteka., M.

[25] Approksimatsiya lineynym ili nelineynym MNK. Kross-platformennaya biblioteka chislennogo analiza ALGLIB [Approximation of linear or nonlinear OLS. Cross-platform biblio-tech numerical analysis ALGLIB] (appeal date: 03/03/2019) http://alglib.sources.ru/interpolation/leastsquares.phpheader0

[26] Bowersox, J. Donald, J. Kloss David, Logistika: integrirovannaya tsep' postavok [Logistics: an integrated supply chain], Per. from English N.N. Baryshnikova, B.S. Pinsker, 2nd ed., ZAO «Olimp-Business», M., 2008, 640 pp.

[27] Yu. A. Korablev, “Razbor prichin i otsenka pogreshnosti anomal'nykh kartin v yemkostnom metode analiza redkikh sobytiy [The causes analysis and error estimation of the anomalous pictures in the capacity method for the analysis of rare events]”, Ekonomika i upravlenie: problemy, resheniya [Economics and Management: problems, solutions], 2017, no. 8 (6), 8–12, Nauchnaya biblioteka., M.