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## Equivalence of Network Structures in Networks of Random Variables with Known and Unknown Shift Parameter

It is proved that sign network with elliptical distribution with known shift parameter is equivalent

to sign network with elliptical distribution with unknown shift parameter estimated as sample mean.

This result is proved for the case of independent identically distributed observation and for the case

of sample from matrix elliptically contoured distribution with any dependence between observations.

Invariance properties of statistical procedures for threshold graph identification are considered. An optimal procedure in the class of invariant multiple decision procedures is constructed.

Market network analysis attracts a growing attention last decades. One of the most important problems related with it is the detection of dynamics in market network. In the present paper, the stock market network of stock’s returns is considered. Probability of sign coincidence of stock’s returns is used as the measure of similarity between stocks. Robust (distribution free) multiple testing statistical procedure for testing dynamics of network is proposed. The constructed procedure is applied for German, French, UK, and USA market. It is shown that in most cases where the dynamics is observed it is determined by a small number of hubs in the associated rejection graph.

This book constitutes the proceedings of the 15th International Computer Science Symposium in Russia, CSR 2020, held in Yekaterinburg, Russia, in June 2020.

The 25 full papers and 6 invited papers were carefully reviewed and selected from 49 submissions. The papers cover a broad range of topics, such as: algorithms and data structures; computational complexity, including hardness of approximation and parameterized complexity; randomness in computing, approximation algorithms, fixed-parameter algorithms; combinatorial optimization, constraint satisfaction, operations research; computational geometry; string algorithms; formal languages and automata, including applications to computational linguistics; codes and cryptography; combinatorics in computer science; computational biology; applications of logic to computer science, proof complexity; database theory; distributed computing; fundamentals of machine learning, including learning theory, grammatical inference and neural computing; computational social choice; quantum computing and quantum cryptography; theoretical aspects of big data.

The conference was cancelled as a live conference due to the corona pandemic.

In each node of a network, economy is described by the simple two-period Romer’s model of endogenous growth with production and knowledge externalities. The sum of knowledge levels in the neighbor nodes causes an externality in the production of each node of the network. The game equilibrium in the network is investigated. The agents’ solutions depending on the size of externality are obtained. The uniqueness of inner equilibrium is proved. The role of passive agents in network formation is studied; in particular, the possibilities of adding a passive agent to a regular network, and also of joining of regular networks through nodes with passive agents. It is shown that the sum of knowledge levels in all the nodes decreases under adding of a new link.

Identification of network structures using the finite-size sample has been considered.

The concepts of random variables network and network model, which is a complete weighted

graph, have been introduced. Two types of network structures have been investigated: network

structures with an arbitrary number of elements and network structures with a fixed number

of elements of the network model. The problem of identification of network structures has

been investigated as a multiple testing problem. The risk function of statistical procedures for

identification of network structures can be represented as a linear combination of expected

numbers of incorrectly included elements and incorrectly non-included elements. The sufficient

conditions of optimality for statistical procedures for network structures identification with

an arbitrary number of elements have been given. The concept of statistical uncertainty of

statistical procedures for identification of network structures has been introduced.

This paper considers a network game as follows. In each node of a network, economy is described by the simple two-period Romer’s model of endogenous growth with production and knowledge externalities. The sum of knowledge levels in the neighbor nodes causes an externality in the production of each network node. The concept of node type is introduced and a corresponding typology of networks is suggested. As demonstrated below, all inner equilibria of the game are determined by this typology. For several typologies, the equilibrium knowledge levels are found in explicit form for the nodes that have different positions in the network.

A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.