MAVKA: Program of statistically optimal determination of phenomenological parameters of extrema. Parabolic spline algorithm and analysis of variability of the semi-regular star Z UMa

Andrych, Kateryna D.; Андронов, И. Л.; Chinarova, L. L.

doi:10.30970/jps.24.1902

Cited by 13 publications

(12 citation statements)

References 30 publications

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“…Right: The approximations of the 2000 pseudo-data generated using the bootstrap algorithm. This sample data show much more stable bootstrap approximations than that discussed byAndrych et al (2020a).…”

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confidence: 51%

“…Andrych et al (2015) compared these approximations with the "Asymptotic Parabola" (AP) fits ). The "spline-like" extension of the AP function, is the parabolic spline (PS) (Andrych et al (2020a)). For longer intervals of data, which are extended to opposite nearby extrema (e.g.…”

Section: Algorithms Used In Mavkamentioning

confidence: 99%

“…The "spline-like" extension of the AP function, is the parabolic spline (PS) (Andrych et al (2020a)). For longer intervals of data, which are extended to opposite nearby extrema (e.g.…”

Section: Algorithms Used In Mavkamentioning

confidence: 99%

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Astroinformatics: Statistically Optimal Approximations of Near-Extremal Parts with Application to Variable Stars

Андронов

Andrych

Chinarova

et al. 2020

ComBAO

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The software MAVKA is described, which was elaborated for statistically optimal determination of the characteristics of the extrema of 1000+ variable stars of different types, mainly eclipsing and pulsating. The approximations are phenomenological, but not physical. As often, the discovery of a new variable star is made on time series of a single-filter (single-channel) data, and there is no possibility to determine parameters needed for physical modelling (e.g. temperature, radial velocities, mass ratio of binaries). Besides classical polynomial approximation "AP" (we limited the degree of the polynomial from 2 to 9), there are realized symmetrical approximations (symmetrical polynomials "SP", "wall-supported" horizontal line "WSL" and parabola "WSP", restricted polynomials of non-integer order based on approximations of the functions proposed by Andronov (2012) and Mikulasek (2015) and generally asymmetric functions (asymptotic parabola "AP", parabolic spline "PS", generalized hyperbolic secant function "SECH" and "log-normal-like" "BSK"). This software is a successor of the "Observation Obscurer" with some features for the variable star research, including a block for "running parabola" "RP" scalegram and approximation. Whereas the RP is oriented on approximation of the complete data set. MAVKA is pointed to parts of the light curve close to extrema (including total eclipses and transits of stars and exoplanets). The functions for wider intervals, covering the eclipse totally, were discussed in Andronov (2017). Global and local approximations are reviewed in Andronov (2020). The software is available at http://uavso.org.ua/mavka and https://katerynaandrych.wixsite.com/mavka. We have analyzed the data from own observations, as well as from monitoring obtained at ground-based and space (currently, mainly, TESS) observatories. It may be used for signals of any nature.

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confidence: 51%

Section: Algorithms Used In Mavkamentioning

confidence: 99%

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Astroinformatics: Statistically Optimal Approximations of Near-Extremal Parts with Application to Variable Stars

Андронов

Andrych

Chinarova

et al. 2020

ComBAO

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“…MAVKA was already used in several articles: Savastru et al (2017); Tvardovskyi et al (2017Tvardovskyi et al ( , 2018; Andrych et al (2020). In these papers we used the AAVSO observations of different observers.…”

Section: Real Observationsmentioning

confidence: 99%

MAVKA: Investigation of stellar brightness extrema approximation stability for various methods

Andrych¹,

Tvardovskyi²,

Chinarova³

et al. 2020

caosp

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We developed the software package MAVKA for the determination of characteristics of extrema (moment of extremum, magnitude) and their errors. The program realizes the application of 11 basic functions for approximation of extrema. We tested all these methods in two parts. In the first part we used generated data sets (various smooth curves with noise). We investigated deviations between generated and computed values of moments of extremum and magnitude, as well as execution time for different extrema parameters. In the second part we used real observations of different variable stars using photometric and visual observations from different databases.

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“…Andronov and Kudashkina, 1988). The semi-regular variable Z UMa showed two two-harmonic waves, which lead to a complex bias behaviour (Andrych et al 2020). The parameters were determined using differential corrections.…”

Section: Periodogram Analysismentioning

confidence: 99%

Variable Stars: A Net of Complementary Methods for Time Series Analysis. Application to RY UMa

Andronov,

Chinarova

2019

Preprint

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cyclic change of semi-amplitude of pulsations between 0.01 to 0.37mag, which is interpreted as a bias between the waves with close periods and a beat period of 4000d (11yr). The dominating period has changed from 307.35(8)d before 1993 to 285.26(6)d after 1993. The initial epoch of the maximum brightness for the recent interval is 2454008.8(5). It is suggested that the apparent period switch is due to variability of amplitudes of these two waves and an occasional swap of the dominating wave.

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MAVKA: Program of statistically optimal determination of phenomenological parameters of extrema. Parabolic spline algorithm and analysis of variability of the semi-regular star Z UMa

Cited by 13 publications

References 30 publications

Astroinformatics: Statistically Optimal Approximations of Near-Extremal Parts with Application to Variable Stars

Astroinformatics: Statistically Optimal Approximations of Near-Extremal Parts with Application to Variable Stars

MAVKA: Investigation of stellar brightness extrema approximation stability for various methods

Variable Stars: A Net of Complementary Methods for Time Series Analysis. Application to RY UMa

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