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Parameter Estimation from Time-Series Data with Correlated E

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Parameter Estimation from Time-Series Data with Correlated Errors: A Wavelet-Based Method and its Application to Transit

Postby owlice » Thu Oct 21, 2010 8:29 pm

Parameter Estimation from Time-Series Data with Correlated Errors: A Wavelet-Based Method and its Application to Transit Light Curves

Abstract: We consider the problem of fitting a parametric model to time-series data that are afflicted by correlated noise. The noise is represented by a sum of two stationary Gaussian processes: one that is uncorrelated in time, and another that has a power spectral density varying as $1/f^gamma$. We present an accurate and fast [O(N)] algorithm for parameter estimation based on computing the likelihood in a wavelet basis. The method is illustrated and tested using simulated time-series photometry of exoplanetary transits, with particular attention to estimating the midtransit time. We compare our method to two other methods that have been used in the literature, the time-averaging method and the residual-permutation method. For noise processes that obey our assumptions, the algorithm presented here gives more accurate results for midtransit times and truer estimates of their uncertainties.

Credit: Carter, Joshua A.; Winn, Joshua N.

Site: http://dx.doi.org/10.20356/C4VC7D
http://adsabs.harvard.edu/abs/2009ApJ...704...51C

Bibcode: 2010ascl.soft10039C

ID: ascl:1010.039
Last edited by Ada Coda on Wed Sep 13, 2017 12:31 am, edited 1 time in total.
Reason: Updated code entry.
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owlice
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Re: Parameter Estimation from Time-Series Data with Correlated E

Postby owlice » Mon Oct 12, 2015 8:41 pm

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