Martina Chvosteková

Slovak Academy of Sciences | SAV · Institute of Measurement Science

In this article we deal with simultaneous two-sided tolerance intervals for a univariate linear regression model with independent normally distributed errors. We present a method for determining the intervals derived by the general confidence-set approach (GCSA), i.e. the intervals are constructed based on a specified confidence set for unknown par...

Information-theoretic generalization of Granger causality principle, based on evaluation of conditional mutual information, also known as transfer entropy (CMI/TE), is redefined in the framework of Rényi entropy (RCMI/RTE). Using numerically generated data with a defined causal structure and examples of real data from the climate system, it is demo...

This paper focuses on parameter estimation within the Errors-in-Variables (EIV) model with nonlinear constraints and the determination of associated uncertainties. This is motivated by a collaborative project in nanoscale material characterization, particularly the assessment of material properties like hardness and elasticity through instrumented...

Recent work has paid close attention to the first principle of Granger causality, according to which cause precedes effect. In this context, the question may arise whether the detected direction of causality also reverses after the time reversal of unidirectionally coupled data. Recently, it has been shown that for unidirectionally causally connect...

The paper is temporarily free here: https://authors.elsevier.com/a/1hi4r3QI%7EFZi3- Revisiting the Grassberger–Procaccia algorithm inspires us to introduce an extremely simple estimator of the correlation dimension. For the new estimator, we also provide guidance on determining the extent to which the correlation dimension may be underestimated, g...

Abstract: Rapidly developing methods of causal inference are being extensively applied to analyze electroencephalographic (EEG) measurements. However, there is considerable uncertainty surrounding the interpretation of the results. Is what the methods reflect from brain activity truly causality? In this study, we first simulate a ground-truth causa...

Recent work has paid close attention to the first principle of Granger causality about the cause preceding the effect. In this context, the question may arise as to whether the detected direction of causality will also be reversed after the time-reversal of unidirectionally coupled data. It has been shown recently that in the case of unidirectional...

In this study, the information flow time arrow is investigated for stochastic data defined by vector autoregressive models. The time series are analyzed forward and backward by different Granger causality detection methods. Besides the normal distribution, which is usually required for the validity of Granger causality analysis, several other distr...

The statistical calibration problem treated here consists of constructing the interval estimates for future unobserved values of a univariate explanatory variable corresponding to an unlimited number of future observations of a univariate response variable. An interval estimate is to be computed for a value x of an explanatory variable after observ...

Although Granger causality is a widely used technique to detect the causal relationship between time series, its direct application for nonlinearly modeled data is not appropriate. There have been proposed several extensions to nonlinear cases, but there is no method appropriate for detecting relations between time series in general. We present a n...

Using several methods for detection of causality in time series, we show in a numerical study that coupled chaotic dynamical systems violate the first principle of Granger causality that the cause precedes the effect. While such a violation can be observed in formal applications of time series analysis methods, it cannot occur in nature, due to the...

In this comparative study, six causality detection methods were compared, namely, the Granger vector autoregressive test, the extended Granger test, the kernel version of the Granger test, the conditional mutual information (transfer entropy), the evaluation of cross mappings between state spaces, and an assessment of predictability improvement due...

Human body movement has been under continuous research for many years due to its potential application as a novel biometric system to identify individuals. It is possible to utilize various techniques, not only to obtain requested movement data, but also to analyse movement data. This paper uses functional data analysis on data obtained from 12 vol...

Objective . The aim of this study was to validate a survival analysis assessing the effect of type of rotary system, canal curvature, and instrument size on cyclic resistance. Materials and Methods . Cyclic fatigue testing was carried out in stainless steel artificial canals with radii of curvature of 3 or 5 mm and the angle of curvature of 60 degr...

We deal with the problem of estimating constructing a confidence band for the 100γth percentile line in the multiple linear regression model with independent identically normally distributed errors. A method for computing the exact Scheffé type confidence band over a limited space of the particular covariates region is suggested. A confidence band...

Numerical results for a simple linear regression indicate that the non-simultaneous two-sided tolerance intervals nearly satisfy the condition of multiple-use confidence intervals, see Lee and Mathew (2002), but the numerical computation of the limits of the multiple-use confidence intervals is needed. We modified the Lieberman-Miller method (1963)...

The simultaneous tolerance intervals are important for many measurement pro-cedures. The most common application for simultaneous tolerance intervals is a multiple-use calibration problem; see e.g. Mee et. al. (Technometrics 1991). In this paper we present a brief overview of the methods for constructing simultaneous tolerance intervals in a linear...

In this paper we present an exact likelihood ratio test (LRT) for testing the simple null hypothesis on all parameters of the linear regression model with normally distributed errors. In particular, we consider the simultaneous test for the regression parameters, β, and the error standard deviation, σ. The critical values of the LRT are presented f...