Statistical Method Selection Matters: Vanilla Methods in Regression May Yield Misleading Results
Kalina, Jan
2023 - English The primary aim of this work is to illustrate the importance of the choice of the appropriate methods for the statistical analysis of economic data. Typically, there exist several alternative versions of common statistical methods for every statistical modeling task and the most habitually used (“vanilla”) versions may yield rather misleading results in nonstandard situations. Linear regression is considered here as the most fundamental econometric model. First, the analysis of a world tourism dataset is presented, where the number of international arrivals is modeled for 140 countries of the world as a response of 14 pillars (indicators) of the Travel and Tourism Competitiveness Index. Heteroscedasticity is clearly recognized in the dataset. However, the Aitken estimator, which would be the standard remedy in such a situation, is revealed here to be very inappropriate, regression quantiles represent a much more suitable solution here. The second illustration with artificial data reveals standard regression quantiles to be unsuitable for data contaminated by outlying values, their recently proposed robust version turns out to be much more appropriate. Both illustrations reveal that choosing suitable methods represent an important (and often difficult) part of the analysis of economic data. Keywords: linear regression; assumptions; non-standard situations; robustness; diagnostics Fulltext is available at external website. Statistical Method Selection Matters: Vanilla Methods in Regression May Yield Misleading Results

The primary aim of this work is to illustrate the importance of the choice of the appropriate methods for the statistical analysis of economic data. Typically, there exist several alternative versions ...

Kalina, Jan
Ústav informatiky, 2023

Fractionally Isomorphic Graphs and Graphons
Hladký, Jan; Hng, Eng Keat
2023 - English Fractional isomorphism is a well-studied relaxation of graph isomorphism with a very rich theory. Grebík and Rocha [Combinatorica 42, pp 365–404 (2022)] developed a concept of fractional isomorphism for graphons and proved that it enjoys an analogous theory. In particular, they proved that if two sequences of graphs that are fractionally isomorphic converge to two graphons, then these graphons are fractionally isomorphism. Answering the main question from ibid, we prove the converse of the statement above: If we have two fractionally isomorphic graphons, then there exist sequences of graphs that are fractionally isomorphic converge and converge to these respective graphons. As an easy but convenient corollary of our methods, we get that every regular graphon can be approximated by regular graphs. Keywords: graph; graphon; graph fractional isomorphism Available in digital repository of the ASCR Fractionally Isomorphic Graphs and Graphons

Fractional isomorphism is a well-studied relaxation of graph isomorphism with a very rich theory. Grebík and Rocha [Combinatorica 42, pp 365–404 (2022)] developed a concept of fractional isomorphism ...

Hladký, Jan; Hng, Eng Keat
Ústav informatiky, 2023

DC 5.3 Odhady kovariancí odhadnutého pole koncentrací
Brabec, Marek; Malý, Marek; Malá, Ivana
2023 - Czech BIBLIOGRAFICKÉ ÚDAJE: Výzkumná zpráva č. SS02030031-V95. Praha: ICS CAS, 2023. 22 s. ANOTACE: Obsahem tohoto dokumentu je popis výsledku typu O: SS02030031-V95, Odhady kovariancí odhadnutého prostorového pole koncentrací. Jde o postup odhadu kovariančních parametrů jak samotného latentního Gaussovského prostorového pole, tak o odhad kovariance regresních parametrů v modelu. Dále též formulace modelu malého měřítka vybraného z dříve testovaných variant. Testování algoritmu optimalizace umístění stanic na předvybraném scénáři. Developing estimation of relevant covariance matrix entries for the spatial model as a necessary part for computing pointwise standard errors (as formalizations of local uncertainty for the gridded estimates). They, in turn are precursors for optimization algorithms aimed at measurement network design problems (location of added and/or deleted measurement points). Keywords: spatial estimation; covariances; uncertainty Available at various institutes of the ASCR DC 5.3 Odhady kovariancí odhadnutého pole koncentrací

BIBLIOGRAFICKÉ ÚDAJE: Výzkumná zpráva č. SS02030031-V95. Praha: ICS CAS, 2023. 22 s. ANOTACE: Obsahem tohoto dokumentu je popis výsledku typu O: SS02030031-V95, Odhady kovariancí odhadnutého ...

Brabec, Marek; Malý, Marek; Malá, Ivana
Ústav informatiky, 2023

Some Robust Approaches to Reducing the Complexity of Economic Data
Kalina, Jan
2023 - English The recent advent of complex (and potentially big) data in economics requires modern and effective tools for their analysis including tools for reducing the dimensionality (complexity) of the given data. This paper starts with recalling the importance of Big Data in economics and with characterizing the main categories of dimension reduction techniques. While there have already been numerous techniques for dimensionality reduction available, this work is interested in methods that are robust to the presence of outlying measurements (outliers) in the economic data. Particularly, methods based on implicit weighting assigned to individual observations are developed in this paper. As the main contribution, this paper proposes three novel robust methods of dimension reduction. One method is a dimension reduction within a robust regularized linear regression, namely a sparse version of the least weighted squares estimator. The other two methods are robust versions of feature extraction methods popular in econometrics: robust principal component analysis and robust factor analysis. Keywords: dimensionality reduction; Big Data; variable selection; robustness; sparsity Fulltext is available at external website. Some Robust Approaches to Reducing the Complexity of Economic Data

The recent advent of complex (and potentially big) data in economics requires modern and effective tools for their analysis including tools for reducing the dimensionality (complexity) of the given ...

Kalina, Jan
Ústav informatiky, 2023

The 2022 Election in the United States: Reliability of a Linear Regression Model
Kalina, Jan; Vidnerová, Petra; Večeř, M.
2023 - English In this paper, the 2022 United States election to the House of Representatives is analyzed by means of a linear regression model. After the election process is explained, the popular vote is modeled as a response of 8 predictors (demographic characteristics) on the state-wide level. The main focus is paid to verifying the reliability of two obtained regression models, namely the full model with all predictors and the most relevant submodel found by hypothesis testing (with 4 relevant predictors). Individual topics related to assessing reliability that are used in this study include confidence intervals for predictions, multicollinearity, and also outlier detection. While the predictions in the submodel that includes only relevant predictors are very similar to those in the full model, it turns out that the submodel has better reliability properties compared to the full model, especially in terms of narrower confidence intervals for the values of the popular vote. Keywords: elections results; electoral demography; linear regression; reliability; variability Fulltext is available at external website. The 2022 Election in the United States: Reliability of a Linear Regression Model

In this paper, the 2022 United States election to the House of Representatives is analyzed by means of a linear regression model. After the election process is explained, the popular vote is modeled ...

Kalina, Jan; Vidnerová, Petra; Večeř, M.
Ústav informatiky, 2023

Permutation Flip Processes
Hladký, Jan; Řada, Hanka
2023 - English We introduce a broad class of stochastic processes on permutations which we call flip processes. A single step in these processes is given by a local change on a randomly chosen fixed-sized tuple of the domain. We use the theory of permutons to describe the typical evolution of any such flip process started from any initial permutation. More specifically, we construct trajectories in the space of permutons with the property that if a finite permutation is close to a permuton then for any time it stays with high probability is close to this predicted trajectory. This view allows to study various questions inspired by dynamical systems. Keywords: permutation; permuton; sorting dynamics; flip process Available in digital repository of the ASCR Permutation Flip Processes

We introduce a broad class of stochastic processes on permutations which we call flip processes. A single step in these processes is given by a local change on a randomly chosen fixed-sized tuple of ...

Hladký, Jan; Řada, Hanka
Ústav informatiky, 2023

Spatio-Spectral EEG Patterns in the Source-Reconstructed Space and Relation to Resting-State Networks: An EEG-fMRI Study
Jiříček, Stanislav; Koudelka, V.; Mantini, D.; Mareček, R.; Hlinka, Jaroslav
2022 - English In this work, we present and evaluate a novel EEG-fMRI integration approach combining a spatio-spectral decomposition method and a reliable source localization technique. On the large 72 subjects resting- state hdEEG-fMRI data set we tested the stability of the proposed method in terms of both extracted spatio-spectral patterns(SSPs) as well as their correspondence to the BOLD signal. We also compared the proposed method with the spatio-spectral decomposition in the electrode space as well as well-known occipital alpha correlate in terms of the explained variance of BOLD signal. We showed that the proposed method is stable in terms of extracted patterns and where they correlate with the BOLD signal. Furthermore, we show that the proposed method explains a very similar level of the BOLD signal with the other methods and that the BOLD signal in areas of typical BOLD functional networks is explained significantly more than by a chance. Nevertheless, we didn’t observe a significant relation between our source-space SSPs and the BOLD ICs when spatio-temporally comparing them. Finally, we report several the most stable source space EEG-fMRI patterns together with their interpretation and comparison to the electrode space patterns. Keywords: EEG-fMRI Integration; EEG-informed fMRI; Spatio-spectral Decomposition; Electrical Source Imaging; Independent Component Analysis; Resting State Networks Available in digital repository of the ASCR Spatio-Spectral EEG Patterns in the Source-Reconstructed Space and Relation to Resting-State Networks: An EEG-fMRI Study

In this work, we present and evaluate a novel EEG-fMRI integration approach combining a spatio-spectral decomposition method and a reliable source localization technique. On the large 72 subjects ...

Jiříček, Stanislav; Koudelka, V.; Mantini, D.; Mareček, R.; Hlinka, Jaroslav
Ústav informatiky, 2022

Interaktivní nástroj pro podporu vyhodnocování dat ze standardizovaných testů
Martinková, Patrícia; Potužníková, E.; Netík, Jan
2022 - Czech ZÁKLADNÍ ÚDAJE: Proměny výchovy a vzdělávání a jejich reflexe v pedagogickém výzkumu: Sborník příspěvků XXX. výroční konference České asociace pedagogického výzkumu. Brno: Masarykova univerzita, 2022 - (Švaříček, R., Voňková, H.), s. 29-31. ISBN 978-80-280-0090-5. [ČAPV 2022: Proměny výchovy a vzdělávání a jejich reflexe v pedagogickém výzkumu /30./. Babice / virtual (CZ), 29.08.2022-31.08.2022]. ABSTRAKT: V příspěvku představujeme možnosti využití modulu interaktivního nástroje pro vyhodnocování dat ze znalostních testů na příkladu dat z maturitní zkoušky z matematiky. Představujeme metody pro detekci odlišného fungování položek pro různé typy škol nebo pro porovnání vybrané školy s ostatními. Ukazujeme, že nástroj má potenciál přispět k informovanému využívání dat z testování a rozhodování na úrovni škol i vzdělávací politiky. In this work, we present features of an interactive tool module for supporting analyses of data from achievement tests by presenting an example of data from the Matura (graduation) exam in mathematics. We present methods for detection of different functioning of items for different types of school, or for comparison of a selected school with other schools. We show that the tool has a potential to help with informed use of achievement test data and to support decision making on both the school and the system levels. Keywords: achievement tests; group differences; interactive tool Available at various institutes of the ASCR Interaktivní nástroj pro podporu vyhodnocování dat ze standardizovaných testů

ZÁKLADNÍ ÚDAJE: Proměny výchovy a vzdělávání a jejich reflexe v pedagogickém výzkumu: Sborník příspěvků XXX. výroční konference České asociace pedagogického výzkumu. Brno: Masarykova univerzita, 2022 ...

Martinková, Patrícia; Potužníková, E.; Netík, Jan
Ústav informatiky, 2022

Czech Gathering of Logicians 2022. Book of Abstracts
Haniková, Zuzana; Švejdar, V.; Wannenburg, Johann Joubert
2022 - English Fulltext is available at external website. Czech Gathering of Logicians 2022. Book of Abstracts

Haniková, Zuzana; Švejdar, V.; Wannenburg, Johann Joubert
Ústav informatiky, 2022

Tisková zpráva - měření tepelného komfortu
Geletič, Jan; Lehnert, M.
2022 - Czech Fulltext is available at external website. Tisková zpráva - měření tepelného komfortu

Geletič, Jan; Lehnert, M.
Ústav informatiky, 2022