Number of found documents: 1457
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Statistical analysis of competing risks in an unemployment study
Volf, Petr
2015 - English
This study is concerned with the analysis of dependence of random variables - latent times to events, in a competing risks case. We discuss first the problem of identifiability of marginal and joint distributions of competing random variables. Then, the copula models are utilized in order to express the dependence. Finally, the Gauss copula is used to solution of a real example with unemployment data. Keywords: statistics; competing risks,; copula; unemployment study Fulltext is available at external website.
Statistical analysis of competing risks in an unemployment study

This study is concerned with the analysis of dependence of random variables - latent times to events, in a competing risks case. We discuss first the problem of identifiability of marginal and joint ...

Volf, Petr
Ústav teorie informace a automatizace, 2015

Wavelet Coefficients Energy Redistribution and Heisenberg Principle of Uncertainty
Vošvrda, Miloslav; Schurrer, J.
2015 - English
First part of the paper summarizes Heisenberg Principle of Uncertainty, Wavelet transformation and signal energy. Second part presents Wavelet analysis of Apple Inc. stock daily closing price, showing energy redistribution depending on the Wavelet decomposition level based on the Wavelet choosen for the decomposition and the level of decomposition. Keywords: Heisenberg Principle of Uncertainty; signal energy; Wavelet Transformation; signal entropy Fulltext is available at external website.
Wavelet Coefficients Energy Redistribution and Heisenberg Principle of Uncertainty

First part of the paper summarizes Heisenberg Principle of Uncertainty, Wavelet transformation and signal energy. Second part presents Wavelet analysis of Apple Inc. stock daily closing price, showing ...

Vošvrda, Miloslav; Schurrer, J.
Ústav teorie informace a automatizace, 2015

The Bandwidth Selection in Connection to Option Implied Volatility Extraction
Tichý, T.; Kopa, Miloš; Vitali, S.
2015 - English
Among various kinds of options we can found at the market, some are traded at organized exchanges and therefore are quite liquid, while others are traded only between particular parties. Whereas there is no need to look for a model to price liquid exchange traded options, since their price is generally accepted by the demand and supply, for illiquid or even exotic options new efficient models are still developed. The current market practice is to obtain the implied volatility of liquid options as based on Black-Scholes type (BS hereafter) models. The focus of this paper is to study the behavior of IV and SPD for several kernel functions and with respect to different choices of bandwidth parameter h. Specifically, we show several interesting implications of the change of h on the violation of no arbitrage condition and the total area of SPD under zero. Keywords: implied volatility; state price density; arbitrage opportunity Fulltext is available at external website.
The Bandwidth Selection in Connection to Option Implied Volatility Extraction

Among various kinds of options we can found at the market, some are traded at organized exchanges and therefore are quite liquid, while others are traded only between particular parties. Whereas there ...

Tichý, T.; Kopa, Miloš; Vitali, S.
Ústav teorie informace a automatizace, 2015

Variational Analysis and Its Applications
Červinka, Michal
2015 - English
The purpose of this meeting is to bring together researchers with common interest in the field. There will be opportunities for informal discussions. Graduate students and others beginning their mathematical career are encouraged to participate. Keywords: variational analysis; data applications; geometry Available at various institutes of the ASCR
Variational Analysis and Its Applications

The purpose of this meeting is to bring together researchers with common interest in the field. There will be opportunities for informal discussions. Graduate students and others beginning their ...

Červinka, Michal
Ústav teorie informace a automatizace, 2015

DCTOOL-A2
Bakule, Lubomír; Papík, Martin; Rehák, Branislav
2015 - English
DCTOOL-A2 is a documentation of Matlab routines developed for the design of decentralized control of large scale complex systems in 2015. Keywords: decentralized control; event-triggered networked control systems; large scale complex systems Available at various institutes of the ASCR
DCTOOL-A2

DCTOOL-A2 is a documentation of Matlab routines developed for the design of decentralized control of large scale complex systems in 2015.

Bakule, Lubomír; Papík, Martin; Rehák, Branislav
Ústav teorie informace a automatizace, 2015

Information fusion with functional Bregman divergence
Dedecius, Kamil
2015 - English
The report summarizes the basics of the Bregman divergence, its functional form and potential use for information fusion. Keywords: information fusion; bregman divergence; entropy Fulltext is available at external website.
Information fusion with functional Bregman divergence

The report summarizes the basics of the Bregman divergence, its functional form and potential use for information fusion.

Dedecius, Kamil
Ústav teorie informace a automatizace, 2015

Scenario Generation via L1 Norm
Kaňková, Vlasta
2015 - English
Optimization problems depending on a probability measure correspond to many economic and financial situations. It can be very complicated to solve these problems, especially when the underlying probability measure belongs to continuous type. Consequently, the underlying continuous probability measure is often replaced by discrete one with finite number of atoms (scenario). The aim of the contribution is to deal with the above mentioned approximation in a special form of stochastic optimization problems with an operator of the mathematical expectation in the objective function. The stability results determined by the help of the Wasserstein metric (based on the L_1 norm) are employed to generate approximate distributions Keywords: One-stage stochastic programming problems; multistage stochastic problems; L_1 norm; Wasserstein metric Fulltext is available at external website.
Scenario Generation via L1 Norm

Optimization problems depending on a probability measure correspond to many economic and financial situations. It can be very complicated to solve these problems, especially when the underlying ...

Kaňková, Vlasta
Ústav teorie informace a automatizace, 2015

Influence diagrams for speed profile optimization" computational issues
Vomlel, Jiří; Kratochvíl, Václav
2015 - English
Influence diagrams were applied to diverse decision problems. However, the general theory is still not sufficiently developed if the variables are continuous or hybrid and the utility functions are nonlinear. In this paper, we study computational problems related to the application of influence diagrams to vehicle speed profile optimization and suggest an approximation of the nonlinear utility functions by piecewise linear functions. Keywords: influence diagram; speed profile; optimization Fulltext is available at external website.
Influence diagrams for speed profile optimization" computational issues

Influence diagrams were applied to diverse decision problems. However, the general theory is still not sufficiently developed if the variables are continuous or hybrid and the utility functions are ...

Vomlel, Jiří; Kratochvíl, Václav
Ústav teorie informace a automatizace, 2015

Recursive Estimation of High-Order Markov Chains: Approximation by Finite Mixtures
Kárný, Miroslav
2015 - English
A high-order Markov chain is a universal model of stochastic relations between discrete-valued variables. The exact estimation of its transition probabilities suers from the curse of dimensionality. It requires an excessive amount of informative observations as well as an extreme memory for storing the corresponding su cient statistic. The paper bypasses this problem by considering a rich subset of Markov-chain models, namely, mixtures of low dimensional Markov chains, possibly with external variables. It uses Bayesian approximate estimation suitable for a subsequent decision making under uncertainty. The proposed recursive (sequential, one-pass) estimator updates a product of Dirichlet probability densities (pds) used as an approximate posterior pd, projects the result back to this class of pds and applies an improved data-dependent stabilised forgetting, which counteracts the dangerous accumulation of approximation errors. Keywords: Markov chain; approximate parameter estimation; Bayesian recursive estimation; adaptive systems; Kullback-Leibler divergence; forgetting Available at various institutes of the ASCR
Recursive Estimation of High-Order Markov Chains: Approximation by Finite Mixtures

A high-order Markov chain is a universal model of stochastic relations between discrete-valued variables. The exact estimation of its transition probabilities suers from the curse of dimensionality. ...

Kárný, Miroslav
Ústav teorie informace a automatizace, 2015

Normal and uniform noise - violation of the assumption on noise distribution in model identification
Jirsa, Ladislav; Pavelková, Lenka
2015 - English
Mathematical modelling under uncertainty together with the field of applied statistics represent tools useful in many practical domains. Widely accepted assumption of normal (Gaussian) noise has created the basis for theoretical and algorithmic solutions of respective tasks. However, many continuous variables are strictly bounded and their uncertainty may have origin in various physical processes which causes a non-normal distribution of their noise. Furthermore, adaptation of algorithms based on normal model for identification of models with bounded noise can distort the estimates due to inconsistent handling of uncertainty. This report describes a study to compare results of estimation algorithms based on assumption of normal and uniform noise. Data sequences processed by the algorithms have normal noise bounded by a low limit with respect to standard deviation. We illustrate disparity between noise assumption and a true noise distribution and its influence on the quality of the estimates. It is a part of an effort to develop theory and fast algorithms for estimation with bounded noise, applicable in practice. Keywords: uncertainty; bounded variable; uniform noise; model identification; assumption of normal noise; estimation comparison Fulltext is available at external website.
Normal and uniform noise - violation of the assumption on noise distribution in model identification

Mathematical modelling under uncertainty together with the field of applied statistics represent tools useful in many practical domains. Widely accepted assumption of normal (Gaussian) noise has ...

Jirsa, Ladislav; Pavelková, Lenka
Ústav teorie informace a automatizace, 2015

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