Number of found documents: 1196
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Appearance Acquisition and Analysis of Effect Coatings
Filip, Jiří; Maile, F. J.
2017 - English
Keywords: effect coatings; appearance capturing; polychromatic; particle orientation Fulltext is available at external website.
Appearance Acquisition and Analysis of Effect Coatings

Filip, Jiří; Maile, F. J.
Ústav teorie informace a automatizace, 2017

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

Multi-period Factor Model of a Loan Portfolio
Šmíd, Martin; Dufek, J.
2017 - English
We construct a general dynamic model of losses of a large loan portfolio, secured by collaterals. In the model, the wealth of a debtor and the price of the corresponding collateral depend each on two factors: a common one, having a general distribution, and an individual one, following an AR(1) process. The default of a loan happens if the wealth stops to be su cient for repaying the loan. We show that the mapping transforming the common factors into the probability of default (PD) and the loss given default (LGD) is one-to-one twice continuously differentiable. As the transformation is not analytically tractable, we propose a numerical technique for its computation and demonstrate its accuracy by a numerical study.\nWe show that the results given by our multi-period model may differ signi cantly from\nthose resulting from single-period models, and demonstrate that our model naturally replicates\nthe empirically observed decrease of PDs within a portfolio in time. In addition, we give a formula for the overall loss of the portfolio and, as an example of its application, we formulate a simple optimal scoring decision problem and discuss its solution. Keywords: Credit Risk; Structural Factor Models; Loan Portfolio Management Fulltext is available at external website.
Multi-period Factor Model of a Loan Portfolio

We construct a general dynamic model of losses of a large loan portfolio, secured by collaterals. In the model, the wealth of a debtor and the price of the corresponding collateral depend each on two ...

Šmíd, Martin; Dufek, J.
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

Parametric Optimization and Related Topics XI
Červinka, Michal; Kratochvíl, Václav
2017 - English
Parametric Optimization and Related Topics XI was a conference dedicate to Jiří Outrata on the occasion of his seventieth birthday. The programme for 86 participants from 21 countries was composed of five invited and 77 contributed talks, held in 22 sessions. Keywords: Parametric Optimization; Optimization; Equilibrium Fulltext is available at external website.
Parametric Optimization and Related Topics XI

Parametric Optimization and Related Topics XI was a conference dedicate to Jiří Outrata on the occasion of his seventieth birthday. The programme for 86 participants from 21 countries was composed of ...

Červinka, Michal; Kratochvíl, Václav
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

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

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