Astronomy and Astrophysics – Astrophysics – Earth and Planetary Astrophysics
Scientific paper
2009-09-03
Astronomy and Astrophysics
Astrophysics
Earth and Planetary Astrophysics
Accepted in ApJ. Illustrative code may be found at http://www.mit.edu/~carterja/code/ . 17 pages
Scientific paper
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.
Carter Joshua A.
Winn Joshua N.
No associations
LandOfFree
Parameter Estimation from Time-Series Data with Correlated Errors: A Wavelet-Based Method and its Application to Transit Light Curves does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Parameter Estimation from Time-Series Data with Correlated Errors: A Wavelet-Based Method and its Application to Transit Light Curves, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Parameter Estimation from Time-Series Data with Correlated Errors: A Wavelet-Based Method and its Application to Transit Light Curves will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-35125