Time series analysis in astronomy: Limits and potentialities

R. Vio, N.R. Kristensen, Henrik Madsen, W. Wamsteker

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    In this paper we consider the problem of the limits concerning the physical information that can be extracted from the analysis of one or more time series ( light curves) typical of astrophysical objects. On the basis of theoretical considerations and numerical simulations, we show that with no a priori physical model there are not many possibilities to obtain interpretable results. For this reason, the practice to develop more and more sophisticated statistical methods of time series analysis is not productive. Only techniques of data analysis developed in a specific physical context can be expected to provide useful results. The field of stochastic dynamics appears to be an interesting framework for such an approach. In particular, it is shown that modelling the experimental time series by means of the stochastic differential equations (SDE) represents a valuable tool of analysis. For example, besides a more direct connection between data analysis and theoretical models, in principle the use of SDE permits the analysis of a continuous signal independent of the characteristics ( e. g., frequency, regularity,...) of the sampling with which the experimental time series were obtained. In this respect, an efficient approach based on the extended Kalman filter technique is presented. Its performances and limits are discussed and tested through numerical experiments. Freely downloadable software is made available.
    Original languageEnglish
    JournalAstronomy & Astrophysics
    Volume435
    Issue number2
    Pages (from-to)773-780
    ISSN0004-6361
    Publication statusPublished - 2005

    Keywords

    • methods : data analysis
    • methods : statistical

    Cite this

    Vio, R., Kristensen, N. R., Madsen, H., & Wamsteker, W. (2005). Time series analysis in astronomy: Limits and potentialities. Astronomy & Astrophysics, 435(2), 773-780.
    Vio, R. ; Kristensen, N.R. ; Madsen, Henrik ; Wamsteker, W. / Time series analysis in astronomy: Limits and potentialities. In: Astronomy & Astrophysics. 2005 ; Vol. 435, No. 2. pp. 773-780.
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    title = "Time series analysis in astronomy: Limits and potentialities",
    abstract = "In this paper we consider the problem of the limits concerning the physical information that can be extracted from the analysis of one or more time series ( light curves) typical of astrophysical objects. On the basis of theoretical considerations and numerical simulations, we show that with no a priori physical model there are not many possibilities to obtain interpretable results. For this reason, the practice to develop more and more sophisticated statistical methods of time series analysis is not productive. Only techniques of data analysis developed in a specific physical context can be expected to provide useful results. The field of stochastic dynamics appears to be an interesting framework for such an approach. In particular, it is shown that modelling the experimental time series by means of the stochastic differential equations (SDE) represents a valuable tool of analysis. For example, besides a more direct connection between data analysis and theoretical models, in principle the use of SDE permits the analysis of a continuous signal independent of the characteristics ( e. g., frequency, regularity,...) of the sampling with which the experimental time series were obtained. In this respect, an efficient approach based on the extended Kalman filter technique is presented. Its performances and limits are discussed and tested through numerical experiments. Freely downloadable software is made available.",
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    Vio, R, Kristensen, NR, Madsen, H & Wamsteker, W 2005, 'Time series analysis in astronomy: Limits and potentialities', Astronomy & Astrophysics, vol. 435, no. 2, pp. 773-780.

    Time series analysis in astronomy: Limits and potentialities. / Vio, R.; Kristensen, N.R.; Madsen, Henrik; Wamsteker, W.

    In: Astronomy & Astrophysics, Vol. 435, No. 2, 2005, p. 773-780.

    Research output: Contribution to journalJournal articleResearchpeer-review

    TY - JOUR

    T1 - Time series analysis in astronomy: Limits and potentialities

    AU - Vio, R.

    AU - Kristensen, N.R.

    AU - Madsen, Henrik

    AU - Wamsteker, W.

    PY - 2005

    Y1 - 2005

    N2 - In this paper we consider the problem of the limits concerning the physical information that can be extracted from the analysis of one or more time series ( light curves) typical of astrophysical objects. On the basis of theoretical considerations and numerical simulations, we show that with no a priori physical model there are not many possibilities to obtain interpretable results. For this reason, the practice to develop more and more sophisticated statistical methods of time series analysis is not productive. Only techniques of data analysis developed in a specific physical context can be expected to provide useful results. The field of stochastic dynamics appears to be an interesting framework for such an approach. In particular, it is shown that modelling the experimental time series by means of the stochastic differential equations (SDE) represents a valuable tool of analysis. For example, besides a more direct connection between data analysis and theoretical models, in principle the use of SDE permits the analysis of a continuous signal independent of the characteristics ( e. g., frequency, regularity,...) of the sampling with which the experimental time series were obtained. In this respect, an efficient approach based on the extended Kalman filter technique is presented. Its performances and limits are discussed and tested through numerical experiments. Freely downloadable software is made available.

    AB - In this paper we consider the problem of the limits concerning the physical information that can be extracted from the analysis of one or more time series ( light curves) typical of astrophysical objects. On the basis of theoretical considerations and numerical simulations, we show that with no a priori physical model there are not many possibilities to obtain interpretable results. For this reason, the practice to develop more and more sophisticated statistical methods of time series analysis is not productive. Only techniques of data analysis developed in a specific physical context can be expected to provide useful results. The field of stochastic dynamics appears to be an interesting framework for such an approach. In particular, it is shown that modelling the experimental time series by means of the stochastic differential equations (SDE) represents a valuable tool of analysis. For example, besides a more direct connection between data analysis and theoretical models, in principle the use of SDE permits the analysis of a continuous signal independent of the characteristics ( e. g., frequency, regularity,...) of the sampling with which the experimental time series were obtained. In this respect, an efficient approach based on the extended Kalman filter technique is presented. Its performances and limits are discussed and tested through numerical experiments. Freely downloadable software is made available.

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    KW - methods : statistical

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