Number of found documents: 792
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Analysis of truncated data with application to the operational risk estimation
Volf, Petr
2017 - English
Analysis of operational risk often faces problems arising from the structure of available data, namely of left truncation and occurrence of heavy-tailed loss values. We deal with model given by lognormal dostribution contaminated by the Pareto one and to use of the Cramér-von Mises, Anderson-Darling, and Kolmogorov-Smirnov minimum distance estimators. Analysis is based on MC studies. The main objective is to propose a method of statistical analysis and modeling for the distribution of sum of\nlosses over a given period, particularly of its right quantiles. Keywords: operational risk; statistical analysis; truncated data Fulltext is available at external website.
Analysis of truncated data with application to the operational risk estimation

Analysis of operational risk often faces problems arising from the structure of available data, namely of left truncation and occurrence of heavy-tailed loss values. We deal with model given by ...

Volf, Petr
Ústav teorie informace a automatizace, 2017

Risk-Sensitive Optimality in Markov Games
Sladký, Karel; Martínez Cortés, V. M.
2017 - English
The article is devoted to risk-sensitive optimality in Markov games. Attention is focused on Markov games evolving on communicating Markov chains with two-players with opposite aims. Considering risk-sensitive optimality criteria means that total reward generated by the game is evaluated by exponential utility function with a given risk-sensitive coefficient. In particular, the first player (resp. the secondplayer) tries to maximize (resp. minimize) the long-run risk sensitive average reward. Observe that if the second player is dummy, the problem is reduced to finding optimal policy of the Markov decision chain with the risk-sensitive optimality. Recall that for the risk sensitivity coefficient equal to zero we arrive at traditional optimality criteria. In this article, connections between risk-sensitive and risk-neutral Markov decisionchains and Markov games models are studied using discrepancy functions. Explicit formulae for bounds on the risk-sensitive average long-run reward are reported. Policy iteration algorithm for finding suboptimal policies of both players is suggested. The obtained results are illustrated on numerical example. \n\n\n\n\n\n\n\n Keywords: two-person Markov games; communicating Markov chains; risk-sensitive optimality; dynamic programming Fulltext is available at external website.
Risk-Sensitive Optimality in Markov Games

The article is devoted to risk-sensitive optimality in Markov games. Attention is focused on Markov games evolving on communicating Markov chains with two-players with opposite aims. Considering ...

Sladký, Karel; Martínez Cortés, V. M.
Ústav teorie informace a automatizace, 2017

Flexible Moment Invariant Bases for 2D Scalar and Vector Fields
Bujack, R.; Flusser, Jan
2017 - English
Complex moments have been successfully applied to pattern detection tasks in two-dimensional real, complex, and vector valued functions. In this paper, we review the different bases of rotational moment invariants based on the generator approach with complex monomials. We analyze their properties with respect to independence, completeness, and existence and\npresent superior bases that are optimal with respect to all three criteria for both scalar and vector fields. Keywords: Pattern detection; moment invariants; scalar fields; vector fields; flow fields; generator; basis; complex; monomial Fulltext is available at external website.
Flexible Moment Invariant Bases for 2D Scalar and Vector Fields

Complex moments have been successfully applied to pattern detection tasks in two-dimensional real, complex, and vector valued functions. In this paper, we review the different bases of rotational ...

Bujack, R.; Flusser, Jan
Ústav teorie informace a automatizace, 2017

Avoiding overfitting of models: an application to research data on the Internet videos
Jiroušek, Radim; Krejčová, I.
2017 - English
The problem of overfitting is studied from the perspective of information theory. In this context, data-based model learning can be viewed as a transformation process; a process transforming the information contained in data into the information represented by a model. The overfitting of a model often occurs when one considers an unnecessarily complex model, which usually means that the considered model contains more information than the original data. Thus, using one of the basic laws of information theory saying that any transformation cannot increase the amount of information, we get the basic restriction laid on models constructed from data: A model is acceptable if it does not contain more information than the input data file. Keywords: data-based learning; probabilistic models; information theory; MDL principle; lossless encoding. Fulltext is available at external website.
Avoiding overfitting of models: an application to research data on the Internet videos

The problem of overfitting is studied from the perspective of information theory. In this context, data-based model learning can be viewed as a transformation process; a process transforming the ...

Jiroušek, Radim; Krejčová, I.
Ústav teorie informace a automatizace, 2017

Exact Inference In Robust Econometrics under Heteroscedasticity
Kalina, Jan; Peštová, Barbora
2017 - English
The paper is devoted to the least weighted squares estimator, which is one of highly robust estimators for the linear regression model. Novel permutation tests of heteroscedasticity are proposed. Also the asymptotic behavior of the permutation test statistics of the Goldfeld-Quandt and Breusch-Pagan tests is investigated. A numerical experiment on real economic data is presented, which also shows how to perform a robust prediction model under heteroscedasticity. Theoretical results may be simply extended to the context of multivariate quantiles Keywords: heteroscedasticity; robust statistics; regression; diagnostic tools; economic data Fulltext is available at external website.
Exact Inference In Robust Econometrics under Heteroscedasticity

The paper is devoted to the least weighted squares estimator, which is one of highly robust estimators for the linear regression model. Novel permutation tests of heteroscedasticity are proposed. Also ...

Kalina, Jan; Peštová, Barbora
Ústav teorie informace a automatizace, 2017

Hidden Auto-Conflict in the Theory of Belief Functions
Daniel, M.; Kratochvíl, Václav
2017 - English
Hidden conflicts of belief functions in some cases where the sum of all multiples of conflicting belief masses being equal to zero were observed. Relationships of hidden conflicts and auto-conflicts of belief functions are pointed out. We are focused on hidden auto-conflicts here - on hidden conflicts appearing when three or more numerically same belief functions are combined. Hidden auto-conflict is a kind of internal conflict. Degrees of hidden auto-conflicts and full non-conflictness are defined and analysed. Finally, computational issues of hidden auto-conflicts and non-conflictness are presented. Keywords: Belief functions; Dempster-Shafer theory; Uncertainty; Conflicting belief masses; Internal conflict; Auto-conflict; Hidden-conflict Fulltext is available at external website.
Hidden Auto-Conflict in the Theory of Belief Functions

Hidden conflicts of belief functions in some cases where the sum of all multiples of conflicting belief masses being equal to zero were observed. Relationships of hidden conflicts and auto-conflicts ...

Daniel, M.; Kratochvíl, Václav
Ústav teorie informace a automatizace, 2017

Dynamické označování polohy pro geografické databáze
Plíhal, Jiří
2017 - Czech
Příspěvek se zabývá problematikou dynamického označování poloh v inteligentních dopravních systémech. Tato metoda umožňuje reprezentovat stejné geoprvky v různých mapách, v různých aplikacích a na odlišných SW/HW platformách. Dynamicky označená poloha je vytvořena jako soubor informačních prvků, které obsahují body a jim příslušející atributy. Ke každému bodu přitom může být připojen jeden nebo i více atributů. Standardizací dynamického označování poloh se zabývá norma ISO 17572-3 Inteligentní dopravní systémy (ITS) - Označení poloh pro geografické databáze – část 3: Dynamické označování poloh (dynamický profil). Příspěvek rozvádí a aktualizuje informace poskytnuté v extraktu návrhu technické normy ISO.17572-3. The paper deals with the dynamic location referencing in intelligent transport systems. This method allows representing the same spatial objects in different maps in different applications and on different software/hardware platforms. The dynamically referenced location is formed as a set of information elements, which contain the points and their corresponding attributes. For each point, one or more attributes can be connected to it at the same time. By standardising dynamic location referencing is engaged in ISO 17572-3 Intelligent Transport Systems (ITS) - Marking positions for geographic databases - Part 3: Dynamic location referencing (dynamic profile). The paper provides updated information about draft ISO 17572-3. Keywords: geographic databases; dynamic location reference; intelligent transport systems Fulltext is available at external website.
Dynamické označování polohy pro geografické databáze

Příspěvek se zabývá problematikou dynamického označování poloh v inteligentních dopravních systémech. Tato metoda umožňuje reprezentovat stejné geoprvky v různých mapách, v různých aplikacích a na ...

Plíhal, Jiří
Ústav teorie informace a automatizace, 2017

A machine learning method for incomplete and imbalanced medical data
Salman, Issam; Vomlel, Jiří
2017 - English
Our research reported in this paper is twofold. In the first part of the paper we use\nstandard statistical methods to analyze medical records of patients suffering myocardial\ninfarction from the third world Syria and a developed country - the Czech Republic.\nOne of our goals is to find whether there are statistically significant differences between\nthe two countries. In the second part of the paper we present an idea how to deal with\nincomplete and imbalanced data for tree-augmented naive Bayesian (TAN). All results\npresented in this paper are based on a real data about 603 patients from a hospital in\nthe Czech Republic and about 184 patients from two hospitals in Syria. Keywords: Machine Learning; Data Analysis; Bayesian networks; Imbalanced Data; Acute Myocardial Infarction Fulltext is available at external website.
A machine learning method for incomplete and imbalanced medical data

Our research reported in this paper is twofold. In the first part of the paper we use\nstandard statistical methods to analyze medical records of patients suffering myocardial\ninfarction from the ...

Salman, Issam; Vomlel, Jiří
Ústav teorie informace a automatizace, 2017

Optimal Value of Loans via Stochastic Programming
Kaňková, Vlasta
2017 - English
A question of mortgage leads to serious and complicated problems of financial mathematics. On one side is a bank with an aim to have a “good” profit, on the other side is the client trying to invest money safely, with possible “small” risk.Let us suppose that a young married couple is in a position of client. Young people know that an expected and also unexpected unpleasant financial situation can happen. Many unpleasant financial situation can be caused by a random factor. Consequently stochastic methods are suitable to secure against them. The aim of the suggested model is not only to state a maximal reasonable value of loans, but also to endure unpleasant financial period. To this end we employ stochastic optimization theory. A few suitable models will be introduced. The choice of the model depends on environment of the young people. Models will be with “deterministic” constraints, probability constraints, but also with stochastic dominance constraints. The suggested models will be analyzed both from the numerical point of view and from possible method solution based on data. Except static one-objective problem we suggest also multi–objective models. Keywords: Loan-debtor; installments; stochastic programming; probability constraints; second order dominance constraints Fulltext is available at external website.
Optimal Value of Loans via Stochastic Programming

A question of mortgage leads to serious and complicated problems of financial mathematics. On one side is a bank with an aim to have a “good” profit, on the other side is the client trying to invest ...

Kaňková, Vlasta
Ústav teorie informace a automatizace, 2017

Feasibility Study of an Interactive Medical Diagnostic Wikipedia
Grim, Jiří
2016 - English
Considering different application possibilities of product distribution mixtures we have proposed three formal tools in the last years, which can be used to accumulate decision-making know-how from particular diagnostic cases. First, we have developed a structural mixture model to estimate multidimensional probability distributions from incomplete and possibly weighted data vectors. Second, we have shown that the estimated product mixture can be used as a knowledge base for the Probabilistic Expert System (PES) to infer conclusions from definite or even uncertain input information. Finally we have shown that, by using product mixtures, we can exactly optimize sequential decision-making by means of the Shannon formula of conditional informativity. We combine the above statistical tools in the framework of an interactive open-access medical diagnostic system with automatic accumulation of decision-making knowledge. Keywords: Multivariate statistics; Medical diagnostics; Product mixtures; Incomplete data; Sequential classification; EM algorithm Fulltext is available at external website.
Feasibility Study of an Interactive Medical Diagnostic Wikipedia

Considering different application possibilities of product distribution mixtures we have proposed three formal tools in the last years, which can be used to accumulate decision-making know-how from ...

Grim, Jiří
Ústav teorie informace a automatizace, 2016

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