On Exact Heteroscedasticity Testing for Robust Regression
Kalina, Jan; Peštová, Barbora
2016 - 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.
Keywords:
robust estimation; outliers; variance; diagnostic tools; heteroscedasticity
Available in digital repository of the ASCR
On Exact Heteroscedasticity Testing for Robust Regression
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 ...
Robust Regularized Discriminant Analysis Based on Implicit Weighting
Kalina, Jan; Hlinka, Jaroslav
2016 - English
In bioinformatics, regularized linear discriminant analysis is commonly used as a tool for supervised classification problems tailormade for high-dimensional data with the number of variables exceeding the number of observations. However, its various available versions are too vulnerable to the presence of outlying measurements in the data. In this paper, we exploit principles of robust statistics to propose new versions of regularized linear discriminant analysis suitable for highdimensional data contaminated by (more or less) severe outliers. The work exploits a regularized version of the minimum weighted covariance determinant estimator, which is one of highly robust estimators of multivariate location and scatter. The performance of the novel classification methods is illustrated on real data sets with a detailed analysis of data from brain activity research.
Keywords:
high-dimensional data; classification analysis; robustness; outliers; regularization
Available in a digital repository NRGL
Robust Regularized Discriminant Analysis Based on Implicit Weighting
In bioinformatics, regularized linear discriminant analysis is commonly used as a tool for supervised classification problems tailormade for high-dimensional data with the number of variables ...
On Nominal Automata as Models of Java-like Object-Oriented Programs
Suzuki, Tomoyuki
2016 - English
In this paper, we proposed a model of Java-like object-oriented programs as nominal automata and a simple method invocation checker.
Available on request at various institutes of the ASCR
On Nominal Automata as Models of Java-like Object-Oriented Programs
In this paper, we proposed a model of Java-like object-oriented programs as nominal automata and a simple method invocation checker.
New Quasi-Newton Method for Solving Systems of Nonlinear Equations
Lukšan, Ladislav; Vlček, Jan
2016 - English
Keywords:
nonlinear equations; systems of equations; trust-region methods; quasi-Newton methods; adjoint Broyden methods; numerical algorithms; numerical experiments
Available in a digital repository NRGL
New Quasi-Newton Method for Solving Systems of Nonlinear Equations
Neural Networks Between Integer and Rational Weights
Šíma, Jiří
2016 - English
The analysis of the computational power of neural networks with the weight parameters between integer and rational numbers is refined. We study an intermediate model of binary-state neural networks with integer weights, corresponding to finite automata, which is extended with an extra analog unit with rational weights, as already two additional analog units allow for Turing universality. We characterize the languages that are accepted by this model in terms of so-called cut languages which are combined in a certain way by usual string operations. We employ this characterization for proving that the languages accepted by neural networks with an analog unit are context-sensitive and we present an explicit example of such non-context-free languages. In addition, we formulate a sufficient condition when these networks accept only regular languages in terms of quasi-periodicity of parameters derived from their weights.
Keywords:
neural networks; analog unit; rational weight; cut languages; computational power
Available in a digital repository NRGL
Neural Networks Between Integer and Rational Weights
The analysis of the computational power of neural networks with the weight parameters between integer and rational numbers is refined. We study an intermediate model of binary-state neural networks ...
Detection of Differential Item Functioning with Non-Linear Regression: Non-IRT Approach Accounting for Guessing
Drabinová, Adéla; Martinková, Patrícia
2016 - English
In this article, we present a new method for estimation of Item Response Function and for detection of uniform and non-uniform Differential Item Functioning (DIF) in dichotomous items based on Non-Linear Regression (NLR). Proposed method extends Logistic Regression (LR) procedure by including pseudoguessing parameter. NLR technique is compared to LR procedure and Lord’s and Raju’s statistics for three-parameter Item Response Theory (IRT) models in simulation study based on Graduate Management Admission Test. NLR shows superiority in power at low rejection rate over IRT methods and outperforms LR procedure in power for case of uniform DIF detection. Our research suggests that the newly proposed non-IRT procedure is an attractive and user friendly approach to DIF detection.
Keywords:
differential item functioning; non-linear regression; logistic regression; item response theory
Available in a digital repository NRGL
Detection of Differential Item Functioning with Non-Linear Regression: Non-IRT Approach Accounting for Guessing
In this article, we present a new method for estimation of Item Response Function and for detection of uniform and non-uniform Differential Item Functioning (DIF) in dichotomous items based on ...
Discerning Two Words by a Minimum Size Automaton
Wiedermann, Jiří
2016 - English
Keywords:
finite automaton; discerning two words; complexity
Available in a digital repository NRGL
Discerning Two Words by a Minimum Size Automaton
Report on the Last Work by Dr. Erich Nuding
Rohn, Jiří
2016 - English
This is a facsimile copy of a 1994 report on the unpublished last paper by Dr. Erich Nuding. It is being made public here in the hope that even after twenty-two years it may be of interest for researchers working in the area of interval computations because of the intriguing concept of the "fourth modality" which has not been rediscovered during a quarter of century which has elapsed since its original formulation.
Keywords:
set-valued mapping; interval linear equations; solution set; fourth modality
Available in a digital repository NRGL
Report on the Last Work by Dr. Erich Nuding
This is a facsimile copy of a 1994 report on the unpublished last paper by Dr. Erich Nuding. It is being made public here in the hope that even after twenty-two years it may be of interest for ...
Measures for Classification Results Evaluation
Řezanková, Hana; Húsek, Dušan
2015 - English
Keywords:
similarity measures; measures of agreement; success rate of classification
Available in a digital repository NRGL
Measures for Classification Results Evaluation
Causation Entropy Principle and Bayesian Inference to Causal Networks
Coufal, David; Hlinka, Jaroslav
2015 - English
Keywords:
causal links; causation entropy; Bayesian inference
Available in a digital repository NRGL
Causation Entropy Principle and Bayesian Inference to Causal Networks
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