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Bayesian methods for analysis and adaptive scheduling of exoplanet observations

Publication ,  Journal Article
Loredo, TJ; Berger, JO; Chernoff, DF; Clyde, MA; Liu, B
Published in: Statistical Methodology
January 1, 2012

We describe work in progress by a collaboration of astronomers and statisticians developing a suite of Bayesian data analysis tools for extrasolar planet (exoplanet) detection, planetary orbit estimation, and adaptive scheduling of observations. Our work addresses analysis of stellar reflex motion data, where a planet is detected by observing the "wobble" of its host star as it responds to the gravitational tug of the orbiting planet. Newtonian mechanics specifies an analytical model for the resulting time series, but it is strongly nonlinear, yielding complex, multimodal likelihood functions; it is even more complex when multiple planets are present. The number of dimensions in the model parameter space ranges from a few to dozens, depending on the number of planets in the system, and the type of motion measured (line-of-sight velocity, or position on the sky). Since orbits are periodic, Bayesian generalizations of periodogram methods facilitate the analysis. This relies on the model being linearly separable, enabling partial analytical marginalization, reducing the dimension of the parameter space. Subsequent analysis uses adaptive Markov chain Monte Carlo methods and adaptive importance sampling to perform the integrals required for both inference (planet detection and orbit measurement), and information-maximizing sequential design (for adaptive scheduling of observations). We present an overview of our current techniques and highlight directions being explored by ongoing research. © 2011 Elsevier B.V..

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Published In

Statistical Methodology

DOI

ISSN

1572-3127

Publication Date

January 1, 2012

Volume

9

Issue

1-2

Start / End Page

101 / 114

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 0104 Statistics
 

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Loredo, T. J., Berger, J. O., Chernoff, D. F., Clyde, M. A., & Liu, B. (2012). Bayesian methods for analysis and adaptive scheduling of exoplanet observations. Statistical Methodology, 9(1–2), 101–114. https://doi.org/10.1016/j.stamet.2011.07.005
Loredo, T. J., J. O. Berger, D. F. Chernoff, M. A. Clyde, and B. Liu. “Bayesian methods for analysis and adaptive scheduling of exoplanet observations.” Statistical Methodology 9, no. 1–2 (January 1, 2012): 101–14. https://doi.org/10.1016/j.stamet.2011.07.005.
Loredo TJ, Berger JO, Chernoff DF, Clyde MA, Liu B. Bayesian methods for analysis and adaptive scheduling of exoplanet observations. Statistical Methodology. 2012 Jan 1;9(1–2):101–14.
Loredo, T. J., et al. “Bayesian methods for analysis and adaptive scheduling of exoplanet observations.” Statistical Methodology, vol. 9, no. 1–2, Jan. 2012, pp. 101–14. Scopus, doi:10.1016/j.stamet.2011.07.005.
Loredo TJ, Berger JO, Chernoff DF, Clyde MA, Liu B. Bayesian methods for analysis and adaptive scheduling of exoplanet observations. Statistical Methodology. 2012 Jan 1;9(1–2):101–114.
Journal cover image

Published In

Statistical Methodology

DOI

ISSN

1572-3127

Publication Date

January 1, 2012

Volume

9

Issue

1-2

Start / End Page

101 / 114

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 0104 Statistics