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On Experimental Part of Behavior under Ambiguity
Kratochvíl, Václav; Jiroušek, Radim
2019 - English
People are risk-takers, risk-averse, or neutral. In the literature, one can find experiments illustrating the ambiguity aversion of human decision-makers. Recently, a personal coefficient of ambiguity aversion has been introduced. We have decided to measure the coefficient and its stability during the time. In this paper, we describe performed experiments and their structure to launch a discussion of possible design weaknesses or to suggest other methods of measuring it.
Keywords:
decision making; uncertainty; personal coefficient
Fulltext is available at external website.
On Experimental Part of Behavior under Ambiguity
People are risk-takers, risk-averse, or neutral. In the literature, one can find experiments illustrating the ambiguity aversion of human decision-makers. Recently, a personal coefficient of ...
ESP32-CAM – POSTAVME SI OČIČKO
Zajíček, Milan
2019 - Czech
Mikrokontroler ESP32 je možné zakoupit jako vývojovou desku ve spojení s 2Mpixel kamerou OV2640. Tento modul je souhrnně označován ESP32-cam. Tutoriál ukazuje možnost použití uvedeného modulu pro snímání obrazu ve formě statických snímků i videa a možnosti komunikace s okolím, či ukládání dat na SD kartu. Pro komunikaci s PC je použit USB-Serial převodník CP2102. Microcontroller ESP32 can be obtained as a development board with 2Mpixel camera OV2640 together. The trademark of such module is ESP32-cam. Tutorial shows the abbility of the module to take the static pictures and video stream, communications skills and saving the data to the SD card. The USB-serial convertor CP2102 is used as an interface for the communication with PC.
Keywords:
IoT; ESP32; mikrokontroler; video
Fulltext is available at external website.
ESP32-CAM – POSTAVME SI OČIČKO
Mikrokontroler ESP32 je možné zakoupit jako vývojovou desku ve spojení s 2Mpixel kamerou OV2640. Tento modul je souhrnně označován ESP32-cam. Tutoriál ukazuje možnost použití uvedeného modulu pro ...
Application of the Cox regression model with time dependent parameters to unemployment data
Volf, Petr
2019 - English
The contribution deals with the application of statistical survival analysis with the intensity described by a generalized version of Cox regression model with time dependent parameters. A\nmethod of model components non-parametric estimation is recalled, the flexibility of result is assessed with a goodness-of-fit test based on martingale residuals. The application\nconcerns to the real data representing the job opportunities development and reduction, during a given period. The risk of leaving the company is changing in time and depends also on the age of employees and their time with company. Both these covariates are considered and their impact to the risk analyzed.
Keywords:
mathematical statistics; survival analysis; unemployment data
Fulltext is available at external website.
Application of the Cox regression model with time dependent parameters to unemployment data
The contribution deals with the application of statistical survival analysis with the intensity described by a generalized version of Cox regression model with time dependent parameters. A\nmethod of ...
A Robustified Metalearning Procedure for Regression Estimators
Kalina, Jan; Neoral, A.
2019 - English
Metalearning represents a useful methodology for selecting and recommending a suitable algorithm or method for a new dataset exploiting a database of training datasets. While metalearning is potentially beneficial for the analysis of economic data, we must be aware of its instability and sensitivity to outlying measurements (outliers) as well as measurement errors. The aim of this paper is to robustify the metalearning process. First, we prepare some useful theoretical tools exploiting the idea of implicit weighting, inspired by the least weighted squares estimator. These include a robust coefficient of determination, a robust version of mean square error, and a simple rule for outlier detection in linear regression. We perform a metalearning study for recommending the best linear regression estimator for a new dataset (not included in the training database). The prediction of the optimal estimator is learned over a set of 20 real datasets with economic motivation, while the least squares are compared with several (highly) robust estimators. We investigate the effect of variable selection on the metalearning results. If the training as well as validation data are considered after a proper robust variable selection, the metalearning performance is improved remarkably, especially if a robust prediction error is used.
Keywords:
model choice; computational statistics; robustness; variable selection
Fulltext is available at external website.
A Robustified Metalearning Procedure for Regression Estimators
Metalearning represents a useful methodology for selecting and recommending a suitable algorithm or method for a new dataset exploiting a database of training datasets. While metalearning is ...
Two Algorithms for Risk-averse Reformulation of Multi-stage Stochastic Programming Problems
Šmíd, Martin; Kozmík, Václav
2018 - English
Many real-life applications lead to risk-averse multi-stage stochastic problems, therefore effective solution of these problems is of great importance. Many tools can be used to their solution (GAMS, Coin-OR, APML or, for smaller problems, Excel), it is, however, mostly up to researcher to reformulate the problem into its deterministic equivalent. Moreover, such solutions are usually one-time, not easy to modify for different applications. We overcome these problems by providing a front-end software package, written in C++, which enables to enter problem definitions in a way close to their mathematical definition. Creating of a deterministic equivalent (and its solution) is up to the computer. In particular, our code is able to solve linear multi-stage with Multi-period Mean-CVaR or Nested Mean-CVaR criteria. In the present paper, we describe the algorithms, transforming these problems into their deterministic equivalents.
Keywords:
Multi-stage stochastic programming; deterministic equivalent; multi-period CVaR; nested CVaR; optimization algorithm
Fulltext is available at external website.
Two Algorithms for Risk-averse Reformulation of Multi-stage Stochastic Programming Problems
Many real-life applications lead to risk-averse multi-stage stochastic problems, therefore effective solution of these problems is of great importance. Many tools can be used to their solution (GAMS, ...
Problem of competing risks with covariates: Application to an unemployment study
Volf, Petr
2018 - English
The study deals with the methods of statistical analysis in the situation of competing risks in the presence of regression. First, the problem of identification of marginal and joint distributions of competing random variables is recalled. The main objective is then to demonstrate that the parameters and, in particular, the correlation of competing variables, may depend on covariates. The approach is applied to solution of a real example with unemployment data. The model uses the Gauss copula and Cox’s regression model.
Keywords:
statistical analysis; competing risks; unemployment study
Fulltext is available at external website.
Problem of competing risks with covariates: Application to an unemployment study
The study deals with the methods of statistical analysis in the situation of competing risks in the presence of regression. First, the problem of identification of marginal and joint distributions of ...
Automatizovaný softwarový systém pro logopedickou terapii
Paroubková, M.; Bílková, Zuzana; Novozámský, Adam; Dominec, A.; Zitová, Barbara
2018 - Czech
Představení automatizovaného softwarového systému pro logopedickou terapii dětí i dospělých (Assistl). Introduction of an automated software system for speech therapy of children and adults (Assistl).
Keywords:
speech therapy; tongue; motor speech disorders
Fulltext is available at external website.
Automatizovaný softwarový systém pro logopedickou terapii
Představení automatizovaného softwarového systému pro logopedickou terapii dětí i dospělých (Assistl)....
Adaptace programového vybavení pro hodnocení radiologických důsledků mimořádných úniků radionuklidů ze skladů vyhořelého jaderného paliva
Pecha, Petr; Pechová, E.
2018 - Czech
Revize implicitní grupy radionuklidů a rozšíření o typické postulované mimořádné úniky ze skladů vyhořelého paliva. bylo provedeno rozšíření databáze radionuklidů systému HARP o další nejdůležitější dlouhodobé radionuklidy. V zásadě se jednalo o výběr štěpných a aktivačních produktů a dále o transurany ze skupiny aktinidů. Jsou konstatovány velké neurčitosti v odhadech zdrojových členů úniku pro případy vyhořelého paliva. Je provedeno vzájemné srovnání pro obálkové scénáře s výsledky evropského environmentálního kódu COSYMA pro rozšířenou grupu transuranů.. Analysis of implicit group of radionuclides and its extension included nuclides with long half-llive of decay. Selection from spent fuel inventories. Selection from fision products, transurans an actinide group. Estimation of possible uncertainties. Comparison analysis is done betřween HARP and European COSYMA codes.
Keywords:
Spent fuel; discharges from repository; radiological impact
Fulltext is available at external website.
Adaptace programového vybavení pro hodnocení radiologických důsledků mimořádných úniků radionuklidů ze skladů vyhořelého jaderného paliva
Revize implicitní grupy radionuklidů a rozšíření o typické postulované mimořádné úniky ze skladů vyhořelého paliva. bylo provedeno rozšíření databáze radionuklidů systému HARP o další nejdůležitější ...
Heuristics in blind source separation
Kautský, Václav; Štěch, Jakub
2018 - English
This paper deals with application of heuristic algorithms (DEBR, MCRS) in blind source separation (BSS). BSS methods focus on a separation of the (source) signal from a linear mixture. The idea of using heuristic algorithms is introduced on the independent component extraction (ICE) model. The motivation for considering heuristics is to obtain an initial guess needed by many ICE algorithms. Moreover, the comparison of this initialization, and other algorithms accuracy is performed.\n
Keywords:
Blind Source Separation; DEBR; Independent Component Extraction
Fulltext is available at external website.
Heuristics in blind source separation
This paper deals with application of heuristic algorithms (DEBR, MCRS) in blind source separation (BSS). BSS methods focus on a separation of the (source) signal from a linear mixture. The idea of ...
Dynamic Bayesian Networks for the Classification of Sleep Stages
Vomlel, Jiří; Kratochvíl, Václav
2018 - English
Human sleep is traditionally classified into five (or six) stages. The manual classification is time consuming since it requires knowledge of an extensive set of rules from manuals and experienced experts. Therefore automatic classification methods appear useful for this task. In this paper we extend the approach based on Hidden Markov Models by relating certain features not only to the current time slice but also to the previous one. Dynamic Bayesian Networks that results from this generalization are thus capable of modeling features related to state transitions. Experiments on real data revealed that in this way we are able to increase the prediction accuracy.
Keywords:
Dynamic Bayesian Network; Sleep Analysis
Fulltext is available at external website.
Dynamic Bayesian Networks for the Classification of Sleep Stages
Human sleep is traditionally classified into five (or six) stages. The manual classification is time consuming since it requires knowledge of an extensive set of rules from manuals and experienced ...
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