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Studium negaussovských světelných křivek pomocí Karhunenova-Loveho rozvoje
Greškovič, Peter ; Pecháček, Tomáš (advisor) ; Mészáros, Attila (referee)
We present an innovative Bayesian method for estimation of statistical parameters of time series data. This method works by comparing coefficients of Karhunen-Lo\`{e}ve expansion of observed and synthetic data with known parameters. We show one new method for generating synthetic data with prescribed properties and we demonstrate on a numerical example how this method can be used for estimation of physically interesting features in power spectra calculated from observed light curves of some X-ray sources.
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Confronting models of twin peak quasi-periodic oscillations: Mass and spin estimates fixed by neutron star equation of state
Török, G. ; Goluchová, K. ; Urbanec, M. ; Šrámková, E. ; Adámek, K. ; Urbancová, G. ; Pecháček, Tomáš ; Bakala, P. ; Stuchlík, Z. ; Horák, Jiří ; Juryšek, J.
In the work authors compare simplified calculations that assume Kerr background geometry to the detailed calculations considering NS oblateness influence in Hartle-Thorne spacetimes.
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